Designing a Study You Can Defend
Research questions require different forms of evidence depending on what they ask researchers to establish. Learn to distinguish description, comparison, association, prediction, explanation, and causation before choosing your research design.
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Designing a Study You Can Defend
Some research questions require measurements, others require access to people's experiences, and some genuinely need both. Learn how to distinguish these evidential requirements without confusing data types with research designs.
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Designing a Study You Can Defend
A difference observed at two points does not always establish that individuals changed, and change does not automatically establish causation. Learn what temporal evidence your research question requires and how to collect it credibly.
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Designing a Study You Can Defend
Some research questions ask whether an outcome occurs, while others ask how it comes about. Learn when mechanism evidence is necessary, what forms it can take, and how to avoid mistaking an association for an explanation.
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Designing a Study You Can Defend
An intervention may be promising in principle but difficult to deliver in practice. Learn when implementation evidence is necessary, what it can establish, and how to investigate what actually happened during intervention delivery.
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Designing a Study You Can Defend
Observing improvement after an intervention does not necessarily mean the intervention caused it. Learn when effectiveness evidence is needed, what makes a comparison credible, and how to match causal claims to the strength of the research design.
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Designing a Study You Can Defend
An intervention can achieve its intended outcome while creating additional burdens or unintended consequences. Learn when harms and benefits must be investigated together, how to select appropriate measures, and why favorable effectiveness findings may not settle whether an intervention is worthwhile.
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Designing a Study You Can Defend
Establishing whether an outcome occurred is not the same as explaining why it occurred. Learn how these questions differ, what evidence each requires, and when a research design can support both conclusions.
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Designing a Study You Can Defend
Collecting relevant data does not necessarily mean having enough evidence to answer a research question. Learn how to recognize evidentiary gaps, assess whether a design supports the intended conclusion, and determine when a research claim must be narrowed.
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Designing a Study You Can Defend
Quantitative research is appropriate when answering a question requires numerical measurement, estimation, comparison, or statistical analysis. Learn when it is the strongest methodological fit, what it can establish, and when numerical evidence alone may be insufficient.
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Designing a Study You Can Defend
Qualitative research is particularly useful when a question concerns experiences, meanings, practices, interactions, or processes that require contextual interpretation. Learn when it is the strongest methodological fit, what different qualitative approaches can establish, and how to assess the adequacy of qualitative evidence.
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Designing a Study You Can Defend
Using quantitative and qualitative methods together does not automatically improve a study. Learn when mixed methods addresses a genuine evidentiary need, how integration should work, and when one well-designed approach is more defensible.
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Designing a Study You Can Defend
Quantitative research can investigate why outcomes occur, but statistical relationships alone do not establish causal explanations. Learn which quantitative designs can support explanatory claims, how mechanisms can be investigated, and when the available evidence is insufficient.
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Designing a Study You Can Defend
Qualitative research can investigate the extent, intensity, and relative prominence of experiences or practices, but it does not automatically support population-level numerical estimates. Learn when qualitative evidence can answer a how much question and when quantitative measurement is necessary.
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Designing a Study You Can Defend
Access to surveys, interviews, institutional records, and other data can create opportunities for mixed-methods research, but availability alone is not a methodological rationale. Learn how to assess whether existing datasets address a shared research problem, can be integrated meaningfully, and justify the additional analytical complexity.
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Designing a Study You Can Defend
Reviewers may recommend adding interviews, surveys, or another methodological component to make a study more comprehensive. Learn when such recommendations address genuine evidentiary limitations, when they introduce unnecessary complexity, and how to respond with a defensible methodological rationale.
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Designing a Study You Can Defend
Adding a second methodological component can expand a study's evidence, but it can also introduce weak measurements, superficial analysis, or unsupported explanations. Learn how to recognize underdeveloped mixed-methods components, assess their consequences, and decide whether strengthening or removing a component would produce a more defensible study.
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Designing a Study You Can Defend
Combining quantitative and qualitative approaches can strengthen research, but only when integration contributes meaningfully to the intended answer. Learn when one carefully executed method is more defensible than two poorly connected approaches, how to recognize superficial integration, and what to prioritize when selecting a research design.
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Designing a Study You Can Defend
Researcher competence affects whether a study can be conducted rigorously, but familiarity with a method should not determine the research question. Learn how to balance methodological expertise, training needs, collaboration, and feasibility when choosing between quantitative, qualitative, and mixed-methods approaches.
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Designing a Study You Can Defend
Sample size affects what a study can establish, but it should not automatically determine whether research is quantitative, qualitative, or mixed methods. Learn how to evaluate sample adequacy according to the intended inference, distinguish statistical power from qualitative information power, and select a defensible design when participant access is limited.
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Designing a Study You Can Defend
Research timelines affect what can realistically be observed, measured, and analyzed, but the fastest method is not necessarily the most appropriate. Learn how time constraints influence quantitative, qualitative, and mixed-methods designs, when shorter studies can remain rigorous, and when the research question must be revised.
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Designing a Study You Can Defend
Experimental, quasi-experimental, and observational studies differ mainly in what researchers do with the exposure or intervention and how participants enter comparison conditions. Understanding those differences helps you choose a design that fits both your research question and the strength of inference you hope to make.
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Designing a Study You Can Defend
Cross-sectional research examines a population or phenomenon within a defined point or period, whereas longitudinal research incorporates observations across time to investigate change, development, or temporal patterns. The better choice depends on what your research question requires you to observe.
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Designing a Study You Can Defend
Prospective and retrospective research differ in how the study is positioned relative to the data and events being investigated. The distinction affects measurement control, available data, bias, feasibility, and how researchers should describe their design.
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Designing a Study You Can Defend
Phenomenology, ethnography, grounded theory, and narrative research are not interchangeable labels for interview-based qualitative studies. Each organizes the inquiry around a different purpose, from understanding lived experience to culture, explanatory processes, or stories.
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