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A study period needs scientific justification when time affects what can be observed, compared, or inferred. The relevant question is not simply how long data collection takes, but whether the chosen period matches the phenomenon and research question.
Read Guide →Should your study be quantitative, qualitative, or mixed methods? Learn how to choose a research approach based on the question you need to answer rather than the method you already know.
Read Guide →Knowing a research method well is a genuine advantage, but familiarity should not be the main reason you choose it. The method must first be capable of producing the evidence needed to answer your research question.
Read Guide →Starting with a preferred method is not automatically wrong, but the final study should not exist merely to give that method something to do. A defensible research question must matter independently and require evidence the chosen method can appropriately provide.
Read Guide →The ideal method for a research question may be beyond your current resources, expertise, access, or institutional capacity. The solution is not automatically to abandon the question or substitute whatever method is convenient, but to determine what can change without changing what the study actually claims to answer.
Read Guide →Research questions often need refinement once practical constraints become clear. The problem begins when adaptation no longer makes the original question feasible but instead replaces it with a different, less meaningful question simply because it fits the method you can use.
Read Guide →Qualitative analysis can be labor-intensive, but that is not sufficient reason to replace a qualitative question with a quantitative one. Time should influence the feasibility and scope of a study without determining what kind of evidence the research question requires.
Read Guide →A replication asks whether prior evidence or a previous claim holds up under another test. An extension moves beyond that prior work to investigate something additional, although a single study can deliberately do both.
Read Guide →Using a different population does not automatically make your research a new study. The key question is whether you are testing the same scientific claim in a new population or whether the population change creates a meaningfully different research question.
Read Guide →A replication does not need a completely new research question to make a contribution. A strong justification explains which existing claim remains uncertain, why resolving that uncertainty matters, and how the new study provides evidence the literature does not yet have.
Read Guide →A methodologically weak study can deserve replication, especially when its claim matters and remains influential. The challenge is deciding whether repeating the original design would test the finding or merely reproduce the weakness that made the evidence uncertain.
Read Guide →Original data can be extremely useful when planning and interpreting a replication, but replication normally generates new data rather than reanalyzing the original dataset. The more important question is whether the published methods and available materials provide enough information to conduct an interpretable new test.
Read Guide →A failed replication does not necessarily end the scientific question. Another replication can be valuable when it can distinguish among plausible explanations for the disagreement rather than merely adding a third result to an unresolved dispute.
Read Guide →A literature full of studies does not necessarily need another dataset. When existing evidence has never been synthesized properly, the first research gap may be a synthesis gap rather than a data gap.
Read Guide →Another primary study is not always the best way to reduce uncertainty. When sufficiently comparable studies already exist, meta-analysis may provide a more precise and informative answer, but only if pooling them is methodologically defensible.
Read Guide →A strong research question is not enough to guarantee a viable study. Stress-test your idea against its assumptions, evidence, recruitment, data, methods, resources, and likely contribution before investing heavily in it.
Read Guide →Before defending a proposed study, try to construct the strongest credible argument against doing it. A serious objection can expose weaknesses in the rationale, evidence, contribution, design, feasibility, or assumptions while there is still time to respond.
Read Guide →Every research idea depends on things being true, available, measurable, or feasible that the study may not directly test. Making those assumptions explicit can reveal which ones are harmless working premises and which could undermine the entire project.
Read Guide →If the relationship you expect does not appear, your study has not automatically failed. The important question is whether the evidence meaningfully challenges the expected relationship or whether the study remains too uncertain to tell.
Read Guide →A worthwhile study should not depend entirely on producing the result you hope to find. Before collecting data, ask what would actually be learned if the main relationship, difference, or effect turns out to be null.
Read Guide →Recruiting fewer participants than expected can affect far more than your sample-size target. Determine what lower recruitment means for precision, representation, timelines, resources, and whether the study can still answer its research question.
Read Guide →Having data is not the same as having data capable of answering your research question. If the data turn out to be incomplete, inaccurate, inconsistent, poorly measured, or otherwise unsuitable, determine what can be repaired, what requires a narrower claim, and what makes the study no longer viable.
Read Guide →Losing access to your preferred method does not automatically mean losing the research idea. Return to the research question, identify what evidence the original method was supposed to provide, and determine whether another defensible approach can still produce the answer you need.
Read Guide →Research does not become unnecessary merely because you expect the same result as previous studies. The real question is whether another study would meaningfully increase confidence, precision, generalizability, theoretical understanding, or the usefulness of the existing evidence.
Read Guide →The study you first imagine is not necessarily the best way to answer your research question. Compare alternative designs by the evidence they can produce, the assumptions they require, and the time, participants, data, and resources they consume.
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