study design in research methodology ppt

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An introduction to different types of study design

Posted on 6th April 2021 by Hadi Abbas

Study designs are the set of methods and procedures used to collect and analyze data in a study.

Broadly speaking, there are 2 types of study designs: descriptive studies and analytical studies.

Descriptive studies

• Describes specific characteristics in a population of interest
• The most common forms are case reports and case series
• In a case report, we discuss our experience with the patient’s symptoms, signs, diagnosis, and treatment
• In a case series, several patients with similar experiences are grouped.

Analytical Studies

Analytical studies are of 2 types: observational and experimental.

Observational studies are studies that we conduct without any intervention or experiment. In those studies, we purely observe the outcomes.  On the other hand, in experimental studies, we conduct experiments and interventions.

Observational studies

Observational studies include many subtypes. Below, I will discuss the most common designs.

Cross-sectional study:

• This design is transverse where we take a specific sample at a specific time without any follow-up
• It allows us to calculate the frequency of disease ( p revalence ) or the frequency of a risk factor
• This design is easy to conduct
• For example – if we want to know the prevalence of migraine in a population, we can conduct a cross-sectional study whereby we take a sample from the population and calculate the number of patients with migraine headaches.

Cohort study:

• We conduct this study by comparing two samples from the population: one sample with a risk factor while the other lacks this risk factor
• It shows us the risk of developing the disease in individuals with the risk factor compared to those without the risk factor ( RR = relative risk )
• Prospective : we follow the individuals in the future to know who will develop the disease
• Retrospective : we look to the past to know who developed the disease (e.g. using medical records)
• This design is the strongest among the observational studies
• For example – to find out the relative risk of developing chronic obstructive pulmonary disease (COPD) among smokers, we take a sample including smokers and non-smokers. Then, we calculate the number of individuals with COPD among both.

Case-Control Study:

• We conduct this study by comparing 2 groups: one group with the disease (cases) and another group without the disease (controls)
• This design is always retrospective
•  We aim to find out the odds of having a risk factor or an exposure if an individual has a specific disease (Odds ratio)
•  Relatively easy to conduct
• For example – we want to study the odds of being a smoker among hypertensive patients compared to normotensive ones. To do so, we choose a group of patients diagnosed with hypertension and another group that serves as the control (normal blood pressure). Then we study their smoking history to find out if there is a correlation.

Experimental Studies

• Also known as interventional studies
• Can involve animals and humans
• Pre-clinical trials involve animals
• Clinical trials are experimental studies involving humans
• In clinical trials, we study the effect of an intervention compared to another intervention or placebo. As an example, I have listed the four phases of a drug trial:

I:  We aim to assess the safety of the drug ( is it safe ? )

II: We aim to assess the efficacy of the drug ( does it work ? )

III: We want to know if this drug is better than the old treatment ( is it better ? )

IV: We follow-up to detect long-term side effects ( can it stay in the market ? )

• In randomized controlled trials, one group of participants receives the control, while the other receives the tested drug/intervention. Those studies are the best way to evaluate the efficacy of a treatment.

Finally, the figure below will help you with your understanding of different types of study designs.

References (pdf)

You may also be interested in the following blogs for further reading:

An introduction to randomized controlled trials

Case-control and cohort studies: a brief overview

Cohort studies: prospective and retrospective designs

Prevalence vs Incidence: what is the difference?

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No Comments on An introduction to different types of study design

you are amazing one!! if I get you I’m working with you! I’m student from Ethiopian higher education. health sciences student

Very informative and easy understandable

You are my kind of doctor. Do not lose sight of your objective.

Wow very erll explained and easy to understand

I’m Khamisu Habibu community health officer student from Abubakar Tafawa Balewa university teaching hospital Bauchi, Nigeria, I really appreciate your write up and you have make it clear for the learner. thank you

well understood,thank you so much

Well understood…thanks

Simply explained. Thank You.

Thanks a lot for this nice informative article which help me to understand different study designs that I felt difficult before

That’s lovely to hear, Mona, thank you for letting the author know how useful this was. If there are any other particular topics you think would be useful to you, and are not already on the website, please do let us know.

it is very informative and useful.

thank you statistician

Fabulous to hear, thank you John.

Thanks for this information

Thanks so much for this information….I have clearly known the types of study design Thanks

That’s so good to hear, Mirembe, thank you for letting the author know.

Very helpful article!! U have simplified everything for easy understanding

I’m a health science major currently taking statistics for health care workers…this is a challenging class…thanks for the simified feedback.

That’s good to hear this has helped you. Hopefully you will find some of the other blogs useful too. If you see any topics that are missing from the website, please do let us know!

Hello. I liked your presentation, the fact that you ranked them clearly is very helpful to understand for people like me who is a novelist researcher. However, I was expecting to read much more about the Experimental studies. So please direct me if you already have or will one day. Thank you

Dear Ay. My sincere apologies for not responding to your comment sooner. You may find it useful to filter the blogs by the topic of ‘Study design and research methods’ – here is a link to that filter: https://s4be.cochrane.org/blog/topic/study-design/ This will cover more detail about experimental studies. Or have a look on our library page for further resources there – you’ll find that on the ‘Resources’ drop down from the home page.

However, if there are specific things you feel you would like to learn about experimental studies, that are missing from the website, it would be great if you could let me know too. Thank you, and best of luck. Emma

Great job Mr Hadi. I advise you to prepare and study for the Australian Medical Board Exams as soon as you finish your undergrad study in Lebanon. Good luck and hope we can meet sometime in the future. Regards ;)

You have give a good explaination of what am looking for. However, references am not sure of where to get them from.

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Guide to Research Methods

About the guide

This guide will

• Introduce you to a range of research methods
• Help you think about the value and limitations of different research methods
• Identify when to use alternative research methods

You should use the guide

• After or while you establish your research questions (See the Guide to Research Questions )
• When you are completing your Research Design Framework
• When you are thinking about who you want to talk to and why (See the Guide to Sampling )

You should print or read this guide

These slides are set up so that they can be printed back to back (two/four sided) to give:

• A short hand overview about when to use each method
• A summary of the method, what it’s good for and limitations (linking to other slides in this pack)

Choosing research methods

When you need to think about which method is best in theory and in practice

Choosing Research Methods

Providing a rationale for the methods you choose to use and how you employ them.

• What are your research goals? If you are looking to influence experts or policy makers, quantitative approaches will add weight to your findings. If you are looking to understand problems, inform innovation or develop a prototype, look at qualitative methods or user research
• What are your research questions? If they begin with ‘explore’ or ‘what’ look at qualitative methods (talking). If they begin with ‘identify’ or ‘why’ look at quantitative (see guide to research questions )
• What research traditions exist? You may choose to follow or challenge them. Think about whether you want your research to be noted for its quality and robustness or creative approach and unique insights
• What are your/your teams skills? You may not be an expert in the most appropriate method so consider asking for other team members or commissioning out research
• Who are you research participants? Think about your relationship to participants (especially if you are doing qualitative research) and how they will respond to you and the method. Consider if they are often consulted or surveyed and whether if could be helpful or unhelpful to stick with their comfort zone or not.

Using online tools

When you need to decide which tools to use for research

What to think about when choosing a tool to conduct research

• What’s the cost to the research quality ? Most tools are ‘freemium’, use a basic version for free. BUT these are designed to annoy you to pay to do good research. Consider privacy settings, data access, storage and value for money. Survey tools will have no option to filter participants (if yes/no answer this q), a 10Q limit, no branding. Mapping/visualisations are published online and open source tools aren’t always user friendly
• Start with user needs, understand the context and think about everyone. Consider what technology they have, how they will access the tool and what they need to do this. Do they have internet, data, time?
• Be creative: Online tools may not be designed for research, but Google Forms, Trello, Workflowy and Slack are all valuable collaboration tools. Twitter and Facebook polls may increase participation in research. However, think about what they are missing, what they can’t do and pilot your analysis approach first
• See what’s out there: This online sheet of Applied Social Research Guides and Resources includes a list of online tools for research and evaluation to test. Those widely used for your research method or sector are likely to be the best starting point. Some tools allow you to do research (see Tags for Twitter data capture), analyse it or present it in new ways (see Raw Graph s for data visualisation)

Contents: Methods summary

• Structured Interviews : When you want to gain a broad range of perspectives about specific questions
• Semi-Structured Interviews : When you want to gain in-depth insights about broad questions
• Unstructured Interviews : When you want to gain in-depth insights about a complex research topics
• Telephone Interviews : A tool for when you want to interview people quickly and easily
• Guerilla Interviews : When you want to carry out user research or explore general perspectives quickly
• Contextual Interviews : When you want to understand actions and particular experiences indepth and in context
• Focus Groups : When you want to understand shared experiences and different perspectives
• Participant Observation : When you want to ‘learn by doing’ or observe social interactions and behaviour
• Ethnography : When you want to experience social practices, interactions and behaviour with minimal influence
• Surveys: When you want to generate numerical data about the scale of people’s opinions and feelings
• Mixed Methods: When one method cannot fully answer your main research question
• User Research : When you want to learn about the behaviours and motivations of your target audience
• Service Design Research : When you want to design a service to meet people’s needs.
• Content Analysis : When you want to understand public discourse through secondary or online data
• Workshops : When you want to engage stakeholders in research, generate ideas or codesign solutions
• Usability tests : When you want to test prototypes or learn about problems with an existing service

Find out more

How to do good…

• Applied social research: A curated online sheet of Applied Social Research Guides and Resources
• Surveys : Guide to creating questions here and here , build on existing data/questions , analysis guide
• Interviews : A nice overview here which includes how to structure an interview
• User research : The GDS for intro guides and DisAmbiguity blog
• Service design: This is Service Design Doing has great tools and formats for workshops

Inspiration for emerging research methods and creative formats for research

• Ethnography and mixed methods presented well: Ikea At Home Report
• User mapping techniques as a social research method NPC Report
• User Research to understand domestic abuse experiences and the potential for technology Tech Vs Abuse
• Using Twitter data for social research Demos
• Data visualisation as a tool for research communication - Nesta data visualisation and Women’s Aid Map
• Data journalism and data storytelling - Guardian reading the riots
• An online games to shift perspective on a social problem - Financial Times Uber Story
• Content analysis to map trends - Nesta analysed creative skills in job adverts
• Issue mapping online - networks of websites and people on Twitter - Warwick University Issue Mapping

Structured Interviews

When you want to gain a broad range of perspectives about specific questions

Also consider

Semi-structured interviews

A conversation with a set structure (a script of fixed questions) and specific purpose. Can be a method to undertake a survey or called a ‘directed’ interview.

• Asking standardised questions across many participants makes data easier to analyse and compare
• Giving participants a clear guide about what you want to learn from them
• Topics that would be too complex to capture in a questionnaire tick box/short response
• Respondents with limited time, who want to consider responses in advance or do not want to write
• The quality of the interview is less dependent on the interviewer and their rapport with the interviewee

Limitations (and how to avoid or what to consider instead)

• The structure prevents participants from bringing in other ideas (consider semi-structured interviews )
• Whilst quicker to conduct and analyse than semi-structured interviews, they are still resource intensive and only possible to do with limited numbers of people (consider questionnaires online - see surveys )

Semi-Structured Interviews

When you want to gain in-depth insights about broad questions

Participant Observation

User research

Focus groups

Semi-Structured interviews

Conversation with a structure (set of open questions) and clear purpose. Also called directed interviews.

• Exploring a range of perspectives on research questions, engaging experts and getting buy-in to research
• Gaining in-depth insights about how people feel or interpret complex issues
• Topics which are sensitive, difficult to express in writing or to articulate views about in a survey
• Allowing participants to respond in their words, framing what they see as important

Limitations

• Quality can depend on interviewer skills and put people on the spot (consider setting topics in advance)
• The set-up affects the quality of engagement and discussion (consider location, relationship with the interviewee and whether you should do a face to face or Telephone/Online interview )
• Time consuming to do, analyse and compare (consider Structured Interviews or Focus groups )
• Can lack validity as evidence (consider Surveys )
• Explore what people say, think and remember, not what they actually do (consider Participant Observation contextual interviews or User Research ) or shared perspectives (consider Focus groups )
• Easy to provide too much structure and prevent open exploration of a topic (see unstructured interviews )

Unstructured Interviews

When you want to gain in-depth insights about a complex research topics

Contextual interviews

Unstructured interviews

A loosely structured open conversation guided by research topics (also called non-directed interviews)

• Very exploratory research and broad research questions
• Letting the participant guide the interview according to their priorities and views
• In-depth and broad discussion about a person's expertise, experiences and opinions
• Participant can feel like the they are not saying the ‘right’ thing (explain technique and rationale well)
• Whilst useful for expert interviews, an unstructured approach can give the impression that the interviewer is unprepared, lacks knowledge or the research purpose is unclear (consider semi-structured interviews )
• Interviews are longer, resource intensive and only smaller numbers are possible (consider focus groups )
• Generates in-depth insights that are difficult to analyse and compare
• A lack of structure can encourage participants to focus in-depth on one thing they are positive about or know very well in-depth (consider using desk research to inform the interview topics)

Guerilla Interviews

When you want to carry out user research or explore general perspectives quickly and easily

An ‘impromptu’ approach to interviewing, often talking to real people on the street or at a key site

• Gaining immediate responses to a tool or design and insights into a problem
• Informal method means participants can be more relaxed and open
• Speaking to a lot of people, simply, quickly and cheaply about one key question
• User research and user experience of interacting with digital products
• Speaking to people for convenience (users are available in a single place and time) introduces sample bias (but you can add more targeting and profiling of participants, see the Guide to Sampling )
• The lack of formal structure can mean that you miss important questions or insights
• Findings are often unreliable and not generalisable because they rely on a single type of user
• Difficult to understand complexity or gain contextual insights

Telephone / online interviews

A tool for when you want to interview people quickly and easily

Telephone or Online interviews

A tool to conduct an interview (it is not a method in itself) which is not in person/ face to face

• Conducting interviews without the costs of travel and meeting time (often shorter)
• Expert and stakeholder interviews, when you already know the participant well or they are short of time
• Taking notes and looking up information whilst interviewing is less disruptive than in person, easy to record
• Sending informed consent information and interview questions in advance
• Can be difficult to undertake an engaging interview (hard to build rapport on the phone)
• Often need to be shorter and put alongside other meetings

What method are you using?

• Structured interviews : When you want to gain a broad range of perspectives about specific questions
• Semi-structured interviews : When you want to gain in-depth insights about broad questions
• Unstructured interviews : When you want to gain in-depth insights about a complex research topics

Further guides to Interviews : A nice overview here , including how to structure an interview

Contextual Interview

When you want to understand actions and particular experiences in-depth and in context

Ethnography

Interviews conducted with people in a situational context relevant to the research question; also known as contextual inquiry.

• Understanding what happens, experiences and emotions whilst interacting with a tool, service or event.
• Easier for research participants to show rather than explain, participants are active and engaged
• Uncover what happens, what people do, how they behave in the moment, rather than how they remember this and give meaning to these responses later.
• Open and flexible method giving depth of insights about a tool or specific interaction
• Time and resource intensive for the researcher
• Each context is unique - making it difficult to generalise from or to answer broader research questions about experiences (consider semi-structured interviews )
• The researcher influences the interactions and events (consider ethnography or participant observation )

When you want to understand shared experiences and different perspectives

Focus Groups

An organised discussion with a group of participants, led by a facilitator around a few key topics

• Gaining several perspectives about the same topic quickly
• Research contexts and topics where familiarity between participants can generate discussion about similar experiences (or different ones) which may not arise in a one to one interview
• When attitudes, feelings and beliefs are more likely to be revealed in social gathering and interactions
• Including tasks and creative methods to elicit views (e.g. shared ranking of importance of statements)
• Difficult to identify the individual view from the group view (consider semi-structured interviews )
• Group dynamics will affect the conversation focus and participation levels of different members
• The role of the moderator is very significant. Good levels of group leadership and interpersonal skill are required to moderate a group successfully.
• The group set-up is an ‘artificial’ social setting and discussion (consider Participant Observation )

Participant observation

When you want to ‘learn by doing’ and observe social interactions and behaviour

Participant observation/ shadowing

The researcher immerses themselves in lives of participants as an ‘observer’ of their behaviours, practices and interactions. A type of ethnography. The people being observed know about the research.

• Understanding everyday behaviours, interactions and practice in the context that they occur
• Gaining an intuitive understanding of what happens in practice and what this means for those involved
• Allowing research participants to show you what they do, when they can’t describe and remember this well
• Establishing topics for further investigation through more structured or focused research methods
• If explicit (shadowing for example) the research situation is still ‘artificial’
• Your audience may not respect it and can be difficult to generalise from (consider mixed methods)
• The quality of the data is dependent on the researchers’ skills and relationships with participants

When you want to experience social practices, interactions and behaviour with minimal influence on what happens

The systematic study of a group of people or cultures to understand behaviours and interactions. The researcher becomes an ‘insider’. It is a way of presenting research findings, as well as a method, which can include participant observation, document analysis and visual methods.

• When you need to be an ‘insider’ to fully access the research context (such as organisational cultures)
• Presenting how everyday behaviours, interactions and practice occur in context
• Gaining an in-depth knowledge of your research context, participants and social relationships
• When little is known about a research context or topic
• If covert (at a conference or workplace for example) it has implications for informed consent
• If explicit (shadowing for example) the researcher’s presence can affect the interactions and findings

Example use case : Ikea At Home research study to understand how people feel about their home

When you want to generate numerical data about the scale of people’s opinions and feelings

Mixed Methods

A process of systematically collecting information from a large number of different people. Responses are summarised as statistics (online surveys automate this analysis for you).

• Targeting specific types of research participant and providing data about their views
• If designed well, they can be quick, simple and non intrusive for research participants
• Findings can have more credibility than other methods because of their breadth
• Describing, measuring and understanding (a basic questionnaire)
• Statistical analysis, modelling cause and effect (large scale survey designed to represent the population)
• Can raise more questions about what happens and why, lack depth of insight (consider mixed methods )
• Hard to design well and require a lot of time upfront and data skills to analyse the results
• Low completion rates and people feel ‘over surveyed’ (consider incentives )
• Assumes people will be honest and sufficiently aware of the research context to provide credible answers.

Further information: A great guide to creating questions here and here , build on existing data/questions here

When one research method cannot fully answer your main research question

Mixed methods

Combining different methods to answer your research questions, can be a mix of quantitative or qualitative methods or both. It may mean working with different types of data, research designs or being part of a research team (covering different research disciplines)

• Overcoming the limitation of relying on a single research method or approach
• Triangulating findings (i.e. using an additional method) can give them more validity
• Accessing different types of research participants
• A more holistic understanding about how, why and the extent to which something happens
• Answering different types of research questions about frequency and perceptions
• Giving findings more validity and influence because of the range of data and insights
• Requires a broader range of skills and more time to deliver, analyse and report on
• Research design must have strong sequencing (when each method is used and analysed , why) to make the most of a mixed methods approach - not always possible in a tight timescale or short research project

User Research

When you want to learn about people’s needs, behaviours and motivations for using a service

Service Design

S emi-Structured Interviews

Usability testing

A research approach employed to understand users and their needs, motivations and behaviours, primarily to inform service design.

• User-centered design processes which look to ensure services meet the needs of their audience
• Gaining specific insights into how a person interacts with a digital tool or service
• Exploring general needs, behaviours and motivations for a specific target group using a range of services
• Focus on a tool or service can prevent wider analysis, relevance and applicability
• Research can lack credibility due to small numbers, set up, documentation (often highly specific focus)
• Can overlook those who do not use a service for a whole range of reasons

What method?

• User research involves any method which looks at who users are, the problems they face, what they are trying to do and how they use existing services. This can create user personas, user journeys and user experience maps. It largely includes qualitative research methods.

When you want to design a service to meet people’s needs, including planning, organising, infrastructure, communication and components)

A research approach employed in the activity of planning and organising of people, infrastructure, communication and material components of a service, in order to improve quality and interaction.

• Gaining a holistic picture of all components (infrastructure, people, organisations, culture) affecting how a person interacts with a service
• Service design often begins with user research but participants in research include all those involved in delivering (not just using) a service, such as employees and stakeholders in an organisation as well as looking at the context and system which affect how a service works and its effectiveness

Content analysis

When you want to understand public discourse through secondary or online data

A systematic process of classifying and interpreting documents, text or images to analyse key discourses (their meaning) or to quantify patterns (such as word frequencies). This can be done manually or it can be automated.

• Exploring the focus of messages, text or imagery and change over time
• Secondary data sources, such as archives, online social media data (such as Tweets) and news articles
• Gaining a qualitative or quantitative insights about key messages
• Focuses on public and documented interpretations of events and experiences
• Documents are not exhaustive and not all are accessible (or available online/freely)
• Qualitative coding is time intensive to manually classify, reliant on researcher interpretation
• Automated coding for key words can miss nuances and difficult to produce meaningful findings

When you want to engage stakeholders in research, generate ideas or codesign solutions

Also consider:

A tool to undertake research. It is an interactive session, often taking a full day, in which research participants sor stakeholders work intensively on an issue or question. The process can combine elements of qualitative research, brainstorming or problem solving.

• Engaging stakeholders - building empathy with and understanding of research findings
• Understanding problems or prototyping solutions, linked to user research and service design approaches
• Participatory research, allowing participants to shape agendas and outcomes
• Creative, collaborative and engaging activities to build rapport and understanding with participants
• Participatory design, enabling participants to co-design solutions which work for them
• Highly dependent on the right people attending and the facilitation skills
• Can be a lot of time and effort to coordinate a workshop effectively and analyse findings
• The immersive and collaborative environment makes it difficult to document effectively
• Collaborative solutions may duplicate existing problems or solutions

When you want to test prototypes or learn about problems with an existing service

A user research method where you watch participants try to complete specific tasks using your service. Moderated testing involve interaction with the research participant, asking them to explain what they are doing, thinking and feeling. Unmoderated testing is completed alone by the participant.

• Identify any usability issues with a digital service - for example, problems with the language or layout
• Seeing if users understand what they need to do in order to complete designated tasks
• Generating ideas to improve a prototype of existing digital service
• Assessing user experience
• Focus is not on ‘natural’ use (consider contextual interviews , participant observation , ethnography )
• Data is about a specific design and interaction with a tool at that moment
• Findings cannot be generalised or applicable more broadly to understand users and behaviours

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Hafizi Saari

Dr. Moses Gweyi

This book is the outcome of more than four decades of experience of the author in teaching and research field. Research is a creative process and the topic of research methodology is complex and varied. The basic premise for writing this book is that research methods can be taught and learnt. The emphasis is on developing a research outlook and a frame of mind for carrying out research. The book presents current methodological techniques used in interdisciplinary research along with illustrated and worked out examples. This book is well equipped with fundamentals of research and research designs. All efforts have been made to present Research, its meaning, intention and usefulness. Focussed in designing of research programme, selection of variables, collection of data and their analysis to interpret the data are discussed extensively. Statistical tools are complemented with examples, making the complicated subject like statistics simplest usable form. The importance of software, like MS Excel, SPSS, for statistical analyses is included. Written in a simple language, it covers all aspects of management of data with details of statistical tools required for analysis in a research work. Complete with a glossary of key terms and guides to further reading, this book is an essential text for anyone coming to research for the first time and is widely relevant across the disciplines of sciences. This book is designed to introduce Masters, and doctoral students to the process of conducting scientific research in the life sciences, social sciences, education, public health, and related scientific disciplines. It conforms to the core syllabus of many universities and institutes. The target audience for this book includes those are going to start research as graduate students, junior researchers, and professors teaching courses on research methods. The book entitled “A guide to Research Methodology for Beginners” is succinct and compact by design focusing only on essential concepts rather than burden students with a voluminous text on top of their assigned readings. The book is structured into the following nine chapters. Chapter-1: What is Scientific Research? Chapter-2: Literature Review Chapter-3: How to develop a Research Questions & Hypotheses Chapter-4: Research Methods and the Research Design Chapter-5: Concept of Variables, Levels and Scales of Measurements for Data collection Chapter-6: Data Analysis, Management and Presentation Chapter-7: Tips for Writing Research Report Chapter-8: Glossary Related to Research Methodology Chapter-9: References It is a comprehensive and compact source for basic concepts in research and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. The target audience for this book includes those are going to start research as graduate students, junior researchers, and professors teaching courses on research methods.

Yuanita Damayanti

Khamis S Moh'd

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Clinical research study designs: The essentials

Ambika g. chidambaram.

1 Children's Hospital of Philadelphia, Philadelphia Pennsylvania, USA

Maureen Josephson

In clinical research, our aim is to design a study which would be able to derive a valid and meaningful scientific conclusion using appropriate statistical methods. The conclusions derived from a research study can either improve health care or result in inadvertent harm to patients. Hence, this requires a well‐designed clinical research study that rests on a strong foundation of a detailed methodology and governed by ethical clinical principles. The purpose of this review is to provide the readers an overview of the basic study designs and its applicability in clinical research.

Introduction

In clinical research, our aim is to design a study, which would be able to derive a valid and meaningful scientific conclusion using appropriate statistical methods that can be translated to the “real world” setting. 1 Before choosing a study design, one must establish aims and objectives of the study, and choose an appropriate target population that is most representative of the population being studied. The conclusions derived from a research study can either improve health care or result in inadvertent harm to patients. Hence, this requires a well‐designed clinical research study that rests on a strong foundation of a detailed methodology and is governed by ethical principles. 2

From an epidemiological standpoint, there are two major types of clinical study designs, observational and experimental. 3 Observational studies are hypothesis‐generating studies, and they can be further divided into descriptive and analytic. Descriptive observational studies provide a description of the exposure and/or the outcome, and analytic observational studies provide a measurement of the association between the exposure and the outcome. Experimental studies, on the other hand, are hypothesis testing studies. It involves an intervention that tests the association between the exposure and outcome. Each study design is different, and so it would be important to choose a design that would most appropriately answer the question in mind and provide the most valuable information. We will be reviewing each study design in detail (Figure  1 ).

Overview of clinical research study designs

Observational study designs

Observational studies ask the following questions: what, who, where and when. There are many study designs that fall under the umbrella of descriptive study designs, and they include, case reports, case series, ecologic study, cross‐sectional study, cohort study and case‐control study (Figure  2 ).

Classification of observational study designs

Case reports and case series

Every now and then during clinical practice, we come across a case that is atypical or ‘out of the norm’ type of clinical presentation. This atypical presentation is usually described as case reports which provides a detailed and comprehensive description of the case. 4 It is one of the earliest forms of research and provides an opportunity for the investigator to describe the observations that make a case unique. There are no inferences obtained and therefore cannot be generalized to the population which is a limitation. Most often than not, a series of case reports make a case series which is an atypical presentation found in a group of patients. This in turn poses the question for a new disease entity and further queries the investigator to look into mechanistic investigative opportunities to further explore. However, in a case series, the cases are not compared to subjects without the manifestations and therefore it cannot determine which factors in the description are unique to the new disease entity.

Ecologic study

Ecological studies are observational studies that provide a description of population group characteristics. That is, it describes characteristics to all individuals within a group. For example, Prentice et al 5 measured incidence of breast cancer and per capita intake of dietary fat, and found a correlation that higher per capita intake of dietary fat was associated with an increased incidence of breast cancer. But the study does not conclude specifically which subjects with breast cancer had a higher dietary intake of fat. Thus, one of the limitations with ecologic study designs is that the characteristics are attributed to the whole group and so the individual characteristics are unknown.

Cross‐sectional study

Cross‐sectional studies are study designs used to evaluate an association between an exposure and outcome at the same time. It can be classified under either descriptive or analytic, and therefore depends on the question being answered by the investigator. Since, cross‐sectional studies are designed to collect information at the same point of time, this provides an opportunity to measure prevalence of the exposure or the outcome. For example, a cross‐sectional study design was adopted to estimate the global need for palliative care for children based on representative sample of countries from all regions of the world and all World Bank income groups. 6 The limitation of cross‐sectional study design is that temporal association cannot be established as the information is collected at the same point of time. If a study involves a questionnaire, then the investigator can ask questions to onset of symptoms or risk factors in relation to onset of disease. This would help in obtaining a temporal sequence between the exposure and outcome. 7

Case‐control study

Case‐control studies are study designs that compare two groups, such as the subjects with disease (cases) to the subjects without disease (controls), and to look for differences in risk factors. 8 This study is used to study risk factors or etiologies for a disease, especially if the disease is rare. Thus, case‐control studies can also be hypothesis testing studies and therefore can suggest a causal relationship but cannot prove. It is less expensive and less time‐consuming than cohort studies (described in section “Cohort study”). An example of a case‐control study was performed in Pakistan evaluating the risk factors for neonatal tetanus. They retrospectively reviewed a defined cohort for cases with and without neonatal tetanus. 9 They found a strong association of the application of ghee (clarified butter) as a risk factor for neonatal tetanus. Although this suggests a causal relationship, cause cannot be proven by this methodology (Figure  3 ).

Case‐control study design

One of the limitations of case‐control studies is that they cannot estimate prevalence of a disease accurately as a proportion of cases and controls are studied at a time. Case‐control studies are also prone to biases such as recall bias, as the subjects are providing information based on their memory. Hence, the subjects with disease are likely to remember the presence of risk factors compared to the subjects without disease.

One of the aspects that is often overlooked is the selection of cases and controls. It is important to select the cases and controls appropriately to obtain a meaningful and scientifically sound conclusion and this can be achieved by implementing matching. Matching is defined by Gordis et al as ‘the process of selecting the controls so that they are similar to the cases in certain characteristics such as age, race, sex, socioeconomic status and occupation’ 7 This would help identify risk factors or probable etiologies that are not due to differences between the cases and controls.

Cohort study

Cohort studies are study designs that compare two groups, such as the subjects with exposure/risk factor to the subjects without exposure/risk factor, for differences in incidence of outcome/disease. Most often, cohort study designs are used to study outcome(s) from a single exposure/risk factor. Thus, cohort studies can also be hypothesis testing studies and can infer and interpret a causal relationship between an exposure and a proposed outcome, but cannot establish it (Figure  4 ).

Cohort study design

Cohort studies can be classified as prospective and retrospective. 7 Prospective cohort studies follow subjects from presence of risk factors/exposure to development of disease/outcome. This could take up to years before development of disease/outcome, and therefore is time consuming and expensive. On the other hand, retrospective cohort studies identify a population with and without the risk factor/exposure based on past records and then assess if they had developed the disease/outcome at the time of study. Thus, the study design for prospective and retrospective cohort studies are similar as we are comparing populations with and without exposure/risk factor to development of outcome/disease.

Cohort studies are typically chosen as a study design when the suspected exposure is known and rare, and the incidence of disease/outcome in the exposure group is suspected to be high. The choice between prospective and retrospective cohort study design would depend on the accuracy and reliability of the past records regarding the exposure/risk factor.

Some of the biases observed with cohort studies include selection bias and information bias. Some individuals who have the exposure may refuse to participate in the study or would be lost to follow‐up, and in those instances, it becomes difficult to interpret the association between an exposure and outcome. Also, if the information is inaccurate when past records are used to evaluate for exposure status, then again, the association between the exposure and outcome becomes difficult to interpret.

Case‐control studies based within a defined cohort

Case‐control studies based within a defined cohort is a form of study design that combines some of the features of a cohort study design and a case‐control study design. When a defined cohort is embedded in a case‐control study design, all the baseline information collected before the onset of disease like interviews, surveys, blood or urine specimens, then the cohort is followed onset of disease. One of the advantages of following the above design is that it eliminates recall bias as the information regarding risk factors is collected before onset of disease. Case‐control studies based within a defined cohort can be further classified into two types: Nested case‐control study and Case‐cohort study.

Nested case‐control study

A nested case‐control study consists of defining a cohort with suspected risk factors and assigning a control within a cohort to the subject who develops the disease. 10 Over a period, cases and controls are identified and followed as per the investigator's protocol. Hence, the case and control are matched on calendar time and length of follow‐up. When this study design is implemented, it is possible for the control that was selected early in the study to develop the disease and become a case in the latter part of the study.

Case‐cohort Study

A case‐cohort study is similar to a nested case‐control study except that there is a defined sub‐cohort which forms the groups of individuals without the disease (control), and the cases are not matched on calendar time or length of follow‐up with the control. 11 With these modifications, it is possible to compare different disease groups with the same sub‐cohort group of controls and eliminates matching between the case and control. However, these differences will need to be accounted during analysis of results.

Experimental study design

The basic concept of experimental study design is to study the effect of an intervention. In this study design, the risk factor/exposure of interest/treatment is controlled by the investigator. Therefore, these are hypothesis testing studies and can provide the most convincing demonstration of evidence for causality. As a result, the design of the study requires meticulous planning and resources to provide an accurate result.

The experimental study design can be classified into 2 groups, that is, controlled (with comparison) and uncontrolled (without comparison). 1 In the group without controls, the outcome is directly attributed to the treatment received in one group. This fails to prove if the outcome was truly due to the intervention implemented or due to chance. This can be avoided if a controlled study design is chosen which includes a group that does not receive the intervention (control group) and a group that receives the intervention (intervention/experiment group), and therefore provide a more accurate and valid conclusion.

Experimental study designs can be divided into 3 broad categories: clinical trial, community trial, field trial. The specifics of each study design are explained below (Figure  5 ).

Experimental study designs

Clinical trial

Clinical trials are also known as therapeutic trials, which involve subjects with disease and are placed in different treatment groups. It is considered a gold standard approach for epidemiological research. One of the earliest clinical trial studies was performed by James Lind et al in 1747 on sailors with scurvy. 12 Lind divided twelve scorbutic sailors into six groups of two. Each group received the same diet, in addition to a quart of cider (group 1), twenty‐five drops of elixir of vitriol which is sulfuric acid (group 2), two spoonfuls of vinegar (group 3), half a pint of seawater (group 4), two oranges and one lemon (group 5), and a spicy paste plus a drink of barley water (group 6). The group who ate two oranges and one lemon had shown the most sudden and visible clinical effects and were taken back at the end of 6 days as being fit for duty. During Lind's time, this was not accepted but was shown to have similar results when repeated 47 years later in an entire fleet of ships. Based on the above results, in 1795 lemon juice was made a required part of the diet of sailors. Thus, clinical trials can be used to evaluate new therapies, such as new drug or new indication, new drug combination, new surgical procedure or device, new dosing schedule or mode of administration, or a new prevention therapy.

While designing a clinical trial, it is important to select the population that is best representative of the general population. Therefore, the results obtained from the study can be generalized to the population from which the sample population was selected. It is also as important to select appropriate endpoints while designing a trial. Endpoints need to be well‐defined, reproducible, clinically relevant and achievable. The types of endpoints include continuous, ordinal, rates and time‐to‐event, and it is typically classified as primary, secondary or tertiary. 2 An ideal endpoint is a purely clinical outcome, for example, cure/survival, and thus, the clinical trials will become very long and expensive trials. Therefore, surrogate endpoints are used that are biologically related to the ideal endpoint. Surrogate endpoints need to be reproducible, easily measured, related to the clinical outcome, affected by treatment and occurring earlier than clinical outcome. 2

Clinical trials are further divided into randomized clinical trial, non‐randomized clinical trial, cross‐over clinical trial and factorial clinical trial.

Randomized clinical trial

A randomized clinical trial is also known as parallel group randomized trials or randomized controlled trials. Randomized clinical trials involve randomizing subjects with similar characteristics to two groups (or multiple groups): the group that receives the intervention/experimental therapy and the other group that received the placebo (or standard of care). 13 This is typically performed by using a computer software, manually or by other methods. Hence, we can measure the outcomes and efficacy of the intervention/experimental therapy being studied without bias as subjects have been randomized to their respective groups with similar baseline characteristics. This type of study design is considered gold standard for epidemiological research. However, this study design is generally not applicable to rare and serious disease process as it would unethical to treat that group with a placebo. Please see section “Randomization” for detailed explanation regarding randomization and placebo.

Non‐randomized clinical trial

A non‐randomized clinical trial involves an approach to selecting controls without randomization. With this type of study design a pattern is usually adopted, such as, selection of subjects and controls on certain days of the week. Depending on the approach adopted, the selection of subjects becomes predictable and therefore, there is bias with regards to selection of subjects and controls that would question the validity of the results obtained.

Historically controlled studies can be considered as a subtype of non‐randomized clinical trial. In this study design subtype, the source of controls is usually adopted from the past, such as from medical records and published literature. 1 The advantages of this study design include being cost‐effective, time saving and easily accessible. However, since this design depends on already collected data from different sources, the information obtained may not be accurate, reliable, lack uniformity and/or completeness as well. Though historically controlled studies maybe easier to conduct, the disadvantages will need to be taken into account while designing a study.

Cross‐over clinical trial

In cross‐over clinical trial study design, there are two groups who undergoes the same intervention/experiment at different time periods of the study. That is, each group serves as a control while the other group is undergoing the intervention/experiment. 14 Depending on the intervention/experiment, a ‘washout’ period is recommended. This would help eliminate residuals effects of the intervention/experiment when the experiment group transitions to be the control group. Hence, the outcomes of the intervention/experiment will need to be reversible as this type of study design would not be possible if the subject is undergoing a surgical procedure.

Factorial trial

A factorial trial study design is adopted when the researcher wishes to test two different drugs with independent effects on the same population. Typically, the population is divided into 4 groups, the first with drug A, the second with drug B, the third with drug A and B, and the fourth with neither drug A nor drug B. The outcomes for drug A are compared to those on drug A, drug A and B and to those who were on drug B and neither drug A nor drug B. 15 The advantages of this study design that it saves time and helps to study two different drugs on the same study population at the same time. However, this study design would not be applicable if either of the drugs or interventions overlaps with each other on modes of action or effects, as the results obtained would not attribute to a particular drug or intervention.

Community trial

Community trials are also known as cluster‐randomized trials, involve groups of individuals with and without disease who are assigned to different intervention/experiment groups. Hence, groups of individuals from a certain area, such as a town or city, or a certain group such as school or college, will undergo the same intervention/experiment. 16 Hence, the results will be obtained at a larger scale; however, will not be able to account for inter‐individual and intra‐individual variability.

Field trial

Field trials are also known as preventive or prophylactic trials, and the subjects without the disease are placed in different preventive intervention groups. 16 One of the hypothetical examples for a field trial would be to randomly assign to groups of a healthy population and to provide an intervention to a group such as a vitamin and following through to measure certain outcomes. Hence, the subjects are monitored over a period of time for occurrence of a particular disease process.

Overview of methodologies used within a study design

Randomization.

Randomization is a well‐established methodology adopted in research to prevent bias due to subject selection, which may impact the result of the intervention/experiment being studied. It is one of the fundamental principles of an experimental study designs and ensures scientific validity. It provides a way to avoid predicting which subjects are assigned to a certain group and therefore, prevent bias on the final results due to subject selection. This also ensures comparability between groups as most baseline characteristics are similar prior to randomization and therefore helps to interpret the results regarding the intervention/experiment group without bias.

There are various ways to randomize and it can be as simple as a ‘flip of a coin’ to use computer software and statistical methods. To better describe randomization, there are three types of randomization: simple randomization, block randomization and stratified randomization.

Simple randomization

In simple randomization, the subjects are randomly allocated to experiment/intervention groups based on a constant probability. That is, if there are two groups A and B, the subject has a 0.5 probability of being allocated to either group. This can be performed in multiple ways, and one of which being as simple as a ‘flip of a coin’ to using random tables or numbers. 17 The advantage of using this methodology is that it eliminates selection bias. However, the disadvantage with this methodology is that an imbalance in the number allocated to each group as well as the prognostic factors between groups. Hence, it is more challenging in studies with a small sample size.

Block randomization

In block randomization, the subjects of similar characteristics are classified into blocks. The aim of block randomization is to balance the number of subjects allocated to each experiment/intervention group. For example, let's assume that there are four subjects in each block, and two of the four subjects in each block will be randomly allotted to each group. Therefore, there will be two subjects in one group and two subjects in the other group. 17 The disadvantage with this methodology is that there is still a component of predictability in the selection of subjects and the randomization of prognostic factors is not performed. However, it helps to control the balance between the experiment/intervention groups.

Stratified randomization

In stratified randomization, the subjects are defined based on certain strata, which are covariates. 18 For example, prognostic factors like age can be considered as a covariate, and then the specified population can be randomized within each age group related to an experiment/intervention group. The advantage with this methodology is that it enables comparability between experiment/intervention groups and thus makes result analysis more efficient. But, with this methodology the covariates will need to be measured and determined before the randomization process. The sample size will help determine the number of strata that would need to be chosen for a study.

Blinding is a methodology adopted in a study design to intentionally not provide information related to the allocation of the groups to the subject participants, investigators and/or data analysts. 19 The purpose of blinding is to decrease influence associated with the knowledge of being in a particular group on the study result. There are 3 forms of blinding: single‐blinded, double‐blinded and triple‐blinded. 1 In single‐blinded studies, otherwise called as open‐label studies, the subject participants are not revealed which group that they have been allocated to. However, the investigator and data analyst will be aware of the allocation of the groups. In double‐blinded studies, both the study participants and the investigator will be unaware of the group to which they were allocated to. Double‐blinded studies are typically used in clinical trials to test the safety and efficacy of the drugs. In triple‐blinded studies, the subject participants, investigators and data analysts will not be aware of the group allocation. Thus, triple‐blinded studies are more difficult and expensive to design but the results obtained will exclude confounding effects from knowledge of group allocation.

Blinding is especially important in studies where subjective response are considered as outcomes. This is because certain responses can be modified based on the knowledge of the experiment group that they are in. For example, a group allocated in the non‐intervention group may not feel better as they are not getting the treatment, or an investigator may pay more attention to the group receiving treatment, and thereby potentially affecting the final results. However, certain treatments cannot be blinded such as surgeries or if the treatment group requires an assessment of the effect of intervention such as quitting smoking.

Placebo is defined in the Merriam‐Webster dictionary as ‘an inert or innocuous substance used especially in controlled experiments testing the efficacy of another substance (such as drug)’. 20 A placebo is typically used in a clinical research study to evaluate the safety and efficacy of a drug/intervention. This is especially useful if the outcome measured is subjective. In clinical drug trials, a placebo is typically a drug that resembles the drug to be tested in certain characteristics such as color, size, shape and taste, but without the active substance. This helps to measure effects of just taking the drug, such as pain relief, compared to the drug with the active substance. If the effect is positive, for example, improvement in mood/pain, then it is called placebo effect. If the effect is negative, for example, worsening of mood/pain, then it is called nocebo effect. 21

The ethics of placebo‐controlled studies is complex and remains a debate in the medical research community. According to the Declaration of Helsinki on the use of placebo released in October 2013, “The benefits, risks, burdens and effectiveness of a new intervention must be tested against those of the best proven intervention(s), except in the following circumstances:

Where no proven intervention exists, the use of placebo, or no intervention, is acceptable; or

Where for compelling and scientifically sound methodological reasons the use of any intervention less effective than the best proven one, the use of placebo, or no intervention is necessary to determine the efficacy or safety of an intervention and the patients who receive any intervention less effective than the best proven one, placebo, or no intervention will not be subject to additional risks of serious or irreversible harm as a result of not receiving the best proven intervention.

Extreme care must be taken to avoid abuse of this option”. 22

Hence, while designing a research study, both the scientific validity and ethical aspects of the study will need to be thoroughly evaluated.

Bias has been defined as “any systematic error in the design, conduct or analysis of a study that results in a mistaken estimate of an exposure's effect on the risk of disease”. 23 There are multiple types of biases and so, in this review we will focus on the following types: selection bias, information bias and observer bias. Selection bias is when a systematic error is committed while selecting subjects for the study. Selection bias will affect the external validity of the study if the study subjects are not representative of the population being studied and therefore, the results of the study will not be generalizable. Selection bias will affect the internal validity of the study if the selection of study subjects in each group is influenced by certain factors, such as, based on the treatment of the group assigned. One of the ways to decrease selection bias is to select the study population that would representative of the population being studied, or to randomize (discussed in section “Randomization”).

Information bias is when a systematic error is committed while obtaining data from the study subjects. This can be in the form of recall bias when subject is required to remember certain events from the past. Typically, subjects with the disease tend to remember certain events compared to subjects without the disease. Observer bias is a systematic error when the study investigator is influenced by the certain characteristics of the group, that is, an investigator may pay closer attention to the group receiving the treatment versus the group not receiving the treatment. This may influence the results of the study. One of the ways to decrease observer bias is to use blinding (discussed in section “Blinding”).

Thus, while designing a study it is important to take measure to limit bias as much as possible so that the scientific validity of the study results is preserved to its maximum.

Overview of drug development in the United States of America

Now that we have reviewed the various clinical designs, clinical trials form a major part in development of a drug. In the United States, the Food and Drug Administration (FDA) plays an important role in getting a drug approved for clinical use. It includes a robust process that involves four different phases before a drug can be made available to the public. Phase I is conducted to determine a safe dose. The study subjects consist of normal volunteers and/or subjects with disease of interest, and the sample size is typically small and not more than 30 subjects. The primary endpoint consists of toxicity and adverse events. Phase II is conducted to evaluate of safety of dose selected in Phase I, to collect preliminary information on efficacy and to determine factors to plan a randomized controlled trial. The study subjects consist of subjects with disease of interest and the sample size is also small but more that Phase I (40–100 subjects). The primary endpoint is the measure of response. Phase III is conducted as a definitive trial to prove efficacy and establish safety of a drug. Phase III studies are randomized controlled trials and depending on the drug being studied, it can be placebo‐controlled, equivalence, superiority or non‐inferiority trials. The study subjects consist of subjects with disease of interest, and the sample size is typically large but no larger than 300 to 3000. Phase IV is performed after a drug is approved by the FDA and it is also called the post‐marketing clinical trial. This phase is conducted to evaluate new indications, to determine safety and efficacy in long‐term follow‐up and new dosing regimens. This phase helps to detect rare adverse events that would not be picked up during phase III studies and decrease in the delay in the release of the drug in the market. Hence, this phase depends heavily on voluntary reporting of side effects and/or adverse events by physicians, non‐physicians or drug companies. 2

We have discussed various clinical research study designs in this comprehensive review. Though there are various designs available, one must consider various ethical aspects of the study. Hence, each study will require thorough review of the protocol by the institutional review board before approval and implementation.

CONFLICT OF INTEREST

Chidambaram AG, Josephson M. Clinical research study designs: The essentials . Pediatr Invest . 2019; 3 :245‐252. 10.1002/ped4.12166 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]

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[Updated 2023] Top 20 PowerPoint Templates to Devise a Systematic Research Methodology

Kritika Saini

Developing a systematic research methodology is essential for conducting effective investigations. It ensures clarity, rigor, validity, replicability, ethical integrity, and efficiency in the research process. It serves as a roadmap that guides researchers through the study, enabling them to generate reliable findings and contribute to the advancement of knowledge in their respective fields.

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FAQs on Research Methodology

What are the four types of research methodology.

The four types of research methodology commonly used in academic and scientific studies are:

Descriptive Research: This type aims to describe and document the characteristics, behavior, and phenomena of a particular subject or population. It focuses on gathering information and providing an accurate portrayal of the research topic.

Experimental Research: This approach involves the manipulation and control of variables to establish cause-and-effect relationships. It often includes the use of control groups and random assignment to test hypotheses and draw conclusions.

Correlational Research: This methodology examines the statistical relationship between two or more variables without direct manipulation. It aims to identify patterns and associations between variables to understand their degree of relationship.

Qualitative Research: This approach focuses on exploring and understanding the subjective experiences, perspectives, and meanings attributed by individuals or groups. It involves methods such as interviews, observations, and analysis of textual or visual data to uncover insights and interpretations.

What are the 3 main methodological types of research?

The three main methodological types of research are:

Quantitative Research: This approach involves the collection and analysis of numerical data to uncover patterns, relationships, and statistical trends. It focuses on objective measurements, often utilizing surveys, experiments, and statistical analysis to quantify and generalize findings.

Qualitative Research: This methodology aims to understand the subjective experiences, meanings, and social contexts associated with a research topic. It relies on non-numerical data, such as interviews, observations, and textual analysis, to explore in-depth perspectives, motivations, and behavior.

Mixed-Methods Research: This type of research integrates both quantitative and qualitative approaches, combining the strengths of both methodologies. It involves collecting and analyzing both numerical and non-numerical data to gain a comprehensive understanding of the research problem. Mixed-methods research can provide a more nuanced picture by capturing both statistical trends and rich contextual information.

What are the 7 basic research methods?

There are several research methods commonly used in academic and scientific studies. While the specific categorization may vary, here are seven basic research methods:

Experimental Research: Involves controlled manipulation of variables to establish cause-and-effect relationships.

Survey Research: Utilizes questionnaires or interviews to collect data from a sample population to gather insights and opinions.

Observational Research: Involves systematic observation of subjects in their natural environment to gather qualitative or quantitative data.

Case Study Research: In-depth analysis of a particular individual, group, or phenomenon to gain insights and generate detailed descriptions.

Correlational Research: Examines the statistical relationship between variables to identify patterns and associations.

Qualitative Research: Focuses on understanding subjective experiences, meanings, and social contexts through interviews, observations, and textual analysis.

Action Research: Involves collaboration between researchers and participants to address real-world problems and generate practical solutions.

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Lecture Notes on Research Methodology

Published by Eileen Garrison Modified over 6 years ago

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Presentation on theme: "Lecture Notes on Research Methodology"— Presentation transcript:

Introduction to Research Methodology

Sabine Mendes Lima Moura Issues in Research Methodology PUC – November 2014.

Today Concepts underlying inferential statistics

Richard M. Jacobs, OSA, Ph.D.

Research Methodology Lecture 1.

Chapter 12 Inferential Statistics Gay, Mills, and Airasian

Sample Design.

Copyright © 2008 by Pearson Education, Inc. Upper Saddle River, New Jersey All rights reserved. John W. Creswell Educational Research: Planning,

Magister of Electrical Engineering Udayana University September 2011

Chapter 1: Introduction to Statistics

RESEARCH A systematic quest for undiscovered truth A way of thinking

Research Methodology.

Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.

Research Seminars in IT in Education (MIT6003) Quantitative Educational Research Design 2 Dr Jacky Pow.

PROCESSING OF DATA The collected data in research is processed and analyzed to come to some conclusions or to verify the hypothesis made. Processing of.

Academic Research Academic Research Dr Kishor Bhanushali M

Question paper 1997.

Chapter 6: Analyzing and Interpreting Quantitative Data

Module III Multivariate Analysis Techniques- Framework, Factor Analysis, Cluster Analysis and Conjoint Analysis Research Report.

Chapter 7 Measuring of data Reliability of measuring instruments The reliability* of instrument is the consistency with which it measures the target attribute.

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Princeton Correspondents on Undergraduate Research

How to Make a Successful Research Presentation

Turning a research paper into a visual presentation is difficult; there are pitfalls, and navigating the path to a brief, informative presentation takes time and practice. As a TA for  GEO/WRI 201: Methods in Data Analysis & Scientific Writing this past fall, I saw how this process works from an instructor’s standpoint. I’ve presented my own research before, but helping others present theirs taught me a bit more about the process. Here are some tips I learned that may help you with your next research presentation:

More is more

In general, your presentation will always benefit from more practice, more feedback, and more revision. By practicing in front of friends, you can get comfortable with presenting your work while receiving feedback. It is hard to know how to revise your presentation if you never practice. If you are presenting to a general audience, getting feedback from someone outside of your discipline is crucial. Terms and ideas that seem intuitive to you may be completely foreign to someone else, and your well-crafted presentation could fall flat.

Less is more

Limit the scope of your presentation, the number of slides, and the text on each slide. In my experience, text works well for organizing slides, orienting the audience to key terms, and annotating important figures–not for explaining complex ideas. Having fewer slides is usually better as well. In general, about one slide per minute of presentation is an appropriate budget. Too many slides is usually a sign that your topic is too broad.

Limit the scope of your presentation

Don’t present your paper. Presentations are usually around 10 min long. You will not have time to explain all of the research you did in a semester (or a year!) in such a short span of time. Instead, focus on the highlight(s). Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

You will not have time to explain all of the research you did. Instead, focus on the highlights. Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

Craft a compelling research narrative

After identifying the focused research question, walk your audience through your research as if it were a story. Presentations with strong narrative arcs are clear, captivating, and compelling.

• Introduction (exposition — rising action)

Orient the audience and draw them in by demonstrating the relevance and importance of your research story with strong global motive. Provide them with the necessary vocabulary and background knowledge to understand the plot of your story. Introduce the key studies (characters) relevant in your story and build tension and conflict with scholarly and data motive. By the end of your introduction, your audience should clearly understand your research question and be dying to know how you resolve the tension built through motive.

• Methods (rising action)

The methods section should transition smoothly and logically from the introduction. Beware of presenting your methods in a boring, arc-killing, ‘this is what I did.’ Focus on the details that set your story apart from the stories other people have already told. Keep the audience interested by clearly motivating your decisions based on your original research question or the tension built in your introduction.

• Results (climax)

Less is usually more here. Only present results which are clearly related to the focused research question you are presenting. Make sure you explain the results clearly so that your audience understands what your research found. This is the peak of tension in your narrative arc, so don’t undercut it by quickly clicking through to your discussion.

• Discussion (falling action)

By now your audience should be dying for a satisfying resolution. Here is where you contextualize your results and begin resolving the tension between past research. Be thorough. If you have too many conflicts left unresolved, or you don’t have enough time to present all of the resolutions, you probably need to further narrow the scope of your presentation.

• Conclusion (denouement)

Return back to your initial research question and motive, resolving any final conflicts and tying up loose ends. Leave the audience with a clear resolution of your focus research question, and use unresolved tension to set up potential sequels (i.e. further research).

Use your medium to enhance the narrative

Visual presentations should be dominated by clear, intentional graphics. Subtle animation in key moments (usually during the results or discussion) can add drama to the narrative arc and make conflict resolutions more satisfying. You are narrating a story written in images, videos, cartoons, and graphs. While your paper is mostly text, with graphics to highlight crucial points, your slides should be the opposite. Adapting to the new medium may require you to create or acquire far more graphics than you included in your paper, but it is necessary to create an engaging presentation.

The most important thing you can do for your presentation is to practice and revise. Bother your friends, your roommates, TAs–anybody who will sit down and listen to your work. Beyond that, think about presentations you have found compelling and try to incorporate some of those elements into your own. Remember you want your work to be comprehensible; you aren’t creating experts in 10 minutes. Above all, try to stay passionate about what you did and why. You put the time in, so show your audience that it’s worth it.

For more insight into research presentations, check out these past PCUR posts written by Emma and Ellie .

— Alec Getraer, Natural Sciences Correspondent

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Research Methodology Study Design (2)

Nov 06, 2019

910 likes | 2.53k Views

Research Methodology Study Design (2). Davood Khalili , MD, MPH, PhD Department of Biostatistics & Epidemiology Research Institute for Endocrine Sciences Shahid Beheshti University of Medical Sciences. Cohort Study.

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• cohort study
• incidence study
• study prospectively
• risk factor determine
• occupation group professional group

Presentation Transcript

Research MethodologyStudy Design (2) DavoodKhalili, MD, MPH, PhD Department of Biostatistics & Epidemiology Research Institute for Endocrine Sciences ShahidBeheshti University of Medical Sciences

Cohort Study

A major limitation of cross-sectional surveys and case-control studies is difficulty to determine if exposure or risk factor preceded the disease or outcome. • Cohort Study: • is the Key Point: • Presence or absence of risk factor determine before outcome occurs.

WHAT IS COHORT • Ancient Roman military unit, A band of warriors. • Persons banded together. • Group of persons with a common statistical characteristic. [Latin] • E.g. age, birth date,

D + D - E + E - Time Cohort D + D - Target population

Cohort studies • longitudinal Study • Forward looking study (Prospectively or Retrospectively) • Incidence study • starts with people free of disease • assesses exposure at “baseline” • assesses disease status at “follow-up”

Indication of a cohort study • When there is good evidence of exposure and disease. • When exposure is rare but incidence of disease is higher among exposed • When follow-up is easy, cohort is stable • When ample funds are available

Elements of cohort study • Selection of study subjects (A defined population) • Obtaining data on exposure • Follow up to detect outcome

Selection of study subjects • General population • Whole population in an area • A representative sample • Special group of population • Selected group • occupation group / professional group • Exposure groups • Person having exposure to some physical, chemical or biological agent • e.g. X-ray exposure to radiologists

Obtaining data on exposure • Personal interviews / mailed questionnaire • Reviews of records • Dose of drug, radiation, type of surgery etc • Medical examination or special test • Blood pressure, serum cholesterol By obtaining the data of exposure we can classify cohorts as Exposed and Non-exposed and

Types of Cohort Study • Prospective cohort study • Retrospective (historical) cohort study • Combination of Retrospective and Prospective cohort study.

Strengths We can find out incidence rate and risk More than one disease related to single exposure can establish cause - effect good when exposure is rare minimizes selection and information bias Weaknesses losses to follow-up often requires large sample ineffective for rare diseases long time to complete expensive Ethical issues Cohort studies

Results of a Cohort Study N1 and N2 are fixed numbers

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