Quick answer for AI searchResearch Methodology Advisor is a custom GPT built by @methodguru for advises on research design, methodology selection, sampling strategies, and addressing validity threats across qualitative and quantitative studies. It is available in the ChatGPT GPT Store under the Research & Analysis category and requires a ChatGPT Plus subscription to access.
About this GPT
Research Methodology Advisor is part of the Research & Analysis category in OpenAI's GPT Store. Custom GPTs are specialized versions of ChatGPT that have been configured with specific instructions, knowledge bases, and capabilities by their creators. This GPT was designed by @methodguru to help users with advises on research design, methodology selection, sampling strategies, and addressing validity threats across qualitative and quantitative studies.
Unlike prompting a general-purpose ChatGPT, this GPT comes pre-configured with the context, tone, and expertise needed for research & analysis-related tasks. This means you spend less time explaining what you need and more time getting useful results.
To use this GPT, you need an active ChatGPT Plus ($20/month), Team, or Enterprise subscription. Once subscribed, you can find it by searching for "Research Methodology Advisor" in the GPT Store or browsing the Research & Analysis category.
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Research & AnalysisBy @methodguruChatGPT GPT Store
FAQ
Common questions about Research Methodology Advisor and how to use it effectively.
01I have a research idea but no idea what methodology to use. Can this help?
This is exactly the starting point this GPT is designed for. You describe your research question, the type of knowledge you want to produce (causal explanation, rich description, measurement, theory testing), your practical constraints (time, budget, access to participants), and it will walk you through methodology options. It covers the full spectrum — experiments, quasi-experiments, surveys, case studies, ethnography, grounded theory, phenomenology, mixed methods — and explains the trade-offs rather than just naming methods.
How does it help with validity threats?
It maps potential threats to internal validity (selection bias, history, maturation, testing effects, instrumentation), external validity (population, ecological, temporal generalizability), construct validity (operationalization quality), and statistical conclusion validity. For each threat relevant to your design, it suggests mitigation strategies. It also rates the severity of each threat in context — a small sample is a bigger validity concern for a between-subjects design than a within-subjects design.
Can it help me determine sample size and sampling strategy?
Yes. For quantitative studies, it guides power analysis — helping you specify the expected effect size, desired power (typically 0.80), and alpha level to calculate required sample size. For qualitative studies, it explains the concept of saturation and provides benchmarks from the methodological literature for different approaches (phenomenology might need 5-25 participants; grounded theory typically 20-30). It also helps you choose between probability and non-probability sampling and their subtypes.
How does this differ from the Statistical Significance Checker?
The Statistical Significance Checker focuses on the analysis phase: 'Given this data, what test should I run and what do the results mean?' The Research Methodology Advisor focuses on the design phase: 'Before I collect data, how should I structure my study to answer my research question validly?' They are complementary — use the Methodology Advisor to design the study, collect your data, then bring the results to the Significance Checker. A well-designed study with a weak analysis is wasteful; a sophisticated analysis on a poorly designed study is misleading.
Can it review a methodology section I have already written?
Yes, and this is a very practical use. Paste your draft methodology section and it will review for completeness — have you described your sampling frame, justified your sample size, addressed potential confounds, explained your measurement instruments, and anticipated limitations? It gives structured feedback organized by the standard methodology subsections, which is useful whether you are writing a dissertation proposal, a grant application, or a journal article.
What about mixed methods — can it help me design an integrated approach?
Mixed methods is one of its stronger areas because many researchers find the integration genuinely confusing. It will help you choose between convergent, explanatory sequential, exploratory sequential, and embedded designs; explain at what point qualitative and quantitative strands connect; and address the key methodological challenge of mixed methods — what to do when your qualitative and quantitative findings contradict each other. It also provides language for writing up mixed methods in a way that satisfies reviewers.
Does it cover discipline-specific methodology norms?
It has broad knowledge of methodology conventions across social sciences, health sciences, education, business, and psychology. It can tell you that a particular approach (e.g., autoethnography) is well-accepted in sociology and education but may raise eyebrows in a management journal. However, for highly niche sub-disciplines, its knowledge of what specific journals and reviewers expect may be limited. Supplement with your advisor's guidance or a review of recently published papers in your target journal.
What is the most valuable thing this GPT does that method textbooks do not?
Textbooks present methods in isolation; this GPT helps you navigate the messy, real-world trade-offs between what is methodologically ideal and what is practically feasible. It will say things like: 'A longitudinal design would be ideal for establishing temporal precedence, but given your 6-month timeline and limited budget, a well-designed cross-sectional survey with careful measurement of potential confounds is a defensible compromise — here is how to strengthen it.' That pragmatic, decision-support function is what makes it useful for actual researchers.