CASRAI Dictionary

Tag: STROBE

  • The STROBE Statement for Observational Epidemiology

    The STROBE Statement, short for Strengthening the Reporting of Observational Studies in Epidemiology, is a reporting guideline that specifies the information an observational study should include so that readers can judge its validity and reuse its findings. STROBE is a checklist for authors, reviewers and editors; it does not dictate how a study should be designed or analysed, only what must be reported transparently once the work is done.

    Observational studies make up a large share of epidemiological evidence, yet they cannot randomise who is exposed to what. Their credibility therefore rests unusually heavily on the clarity of their reporting, and STROBE exists to make that clarity a shared, citable expectation rather than a matter of individual habit.

    What STROBE covers

    The STROBE checklist enumerates items spanning the standard sections of a research paper: title and abstract, introduction, methods, results and discussion. The methods items are central, asking authors to describe the study setting, eligibility criteria, the variables and how they were measured, the data sources, efforts to address potential sources of bias, how the study size was determined, how confounding was handled, and the statistical methods used. The results items ask for the flow of participants through the study, descriptive data on the participants, and the main estimates reported with measures of uncertainty such as confidence intervals. Several items deal specifically with how the study handled missing data, how continuous variables were grouped or modelled, and whether any sensitivity analyses were performed, because each of these choices can materially change a result and each is easy to leave undescribed. A short, structured abstract is also expected, so that readers scanning the literature can grasp the design, population and main findings before reading the full text.

    The aim is completeness rather than a particular conclusion. When every relevant item is reported, a reader can assess whether the conclusions are supported by the design and data, and another team can attempt to reproduce the work or pool it in a synthesis. This emphasis on transparent, reusable reporting aligns directly with the wider goals of reproducibility in research, where undocumented methods are a primary obstacle to replication.

    Three observational study designs

    STROBE is written to cover the three principal observational designs, with a common core checklist plus design-specific guidance where the designs diverge.

    Design How it observes Typical question
    Cohort Follows groups over time by exposure status What outcomes follow an exposure?
    Case-control Compares exposure histories of cases and controls What exposures preceded an outcome?
    Cross-sectional Measures exposure and outcome at one point What is associated at a given time?

    Because these designs differ in how data are gathered and in the biases they are prone to, certain checklist items are tailored to each. A case-control study, for example, must report carefully how cases and controls were selected, while a cohort study must report how participants were followed and how losses to follow-up were handled. Reporting which design was used, and reporting it accurately, is itself a STROBE requirement and a prerequisite for sound interpretation, since the same association means different things under different designs.

    Extensions and related reporting tools

    The core STROBE checklist has been supplemented by extensions that address particular fields and data types while keeping the same philosophy of transparent reporting. These extensions adapt the checklist for areas such as molecular and genetic epidemiology, nutritional epidemiology, infectious-disease studies and research that reuses routinely collected health data, where additional reporting items are needed to let readers judge validity. The proliferation of extensions reflects a general principle: the more specialised or complex the data source, the more there is to report before a study can be appraised or reproduced. Authors should check whether an extension exists for their study type, because using the most specific applicable guideline captures reporting items that the generic checklist would miss. This mirrors the broader move in research toward documenting not just results but the full provenance of the data and analysis behind them.

    STROBE and the EQUATOR Network

    STROBE is one of the most widely used guidelines hosted by the EQUATOR Network, an international initiative that curates reporting guidelines to improve the reliability and value of the health research literature. EQUATOR organises guidelines by study type, so STROBE sits alongside guidelines such as CONSORT for randomised trials and PRISMA for systematic reviews. Locating a guideline through EQUATOR helps authors choose the correct checklist for their study type rather than reaching for a familiar but inappropriate one.

    Within an evidence ecosystem, having a named, citable reporting standard makes expectations explicit for everyone involved. It also connects observational studies to the population measures they rely on, such as incidence and prevalence and the denominators drawn from a census. Consistent terminology drawn from the CASRAI dictionary further helps keep the language of reporting stable across studies and journals.

    How STROBE is used in practice

    In practice, STROBE is most useful when it is consulted at the writing stage and again at peer review. Authors typically complete the checklist and indicate, for each item, the page or section where it is addressed, submitting this alongside the manuscript so that editors and reviewers can verify coverage quickly. Many journals reference STROBE in their instructions to authors for observational research, which gives the guideline practical force rather than leaving it as an optional ideal. Importantly, STROBE is not a quality score: a study can be reported completely yet still have design limitations, and conversely a strong study reported poorly is hard to trust. The checklist’s role is to ensure that whatever the study did, the reader can see it clearly. Used this way, it improves the appraisal, synthesis and reuse of observational evidence without constraining how researchers choose to investigate their questions.

    Why transparent reporting matters

    Observational studies cannot randomise exposure, so their credibility rests heavily on how clearly the methods, data sources and analytical choices are reported. Incomplete reporting makes it impossible to judge whether bias or confounding could explain the findings, and it makes the work difficult or impossible to reproduce, which weakens the cumulative evidence base. Transparent, STROBE-compliant reporting supports critical appraisal by readers, enables evidence synthesis by reviewers, and allows secondary analysts to reuse the work with confidence. Authors preparing observational manuscripts can consult the guidance for authors to align their reporting with these expectations from the outset rather than retrofitting it at submission.

    Frequently asked questions

    Is STROBE a way to design a study?

    No. STROBE is a reporting guideline, not a design or analysis protocol. It tells authors what to report so readers can evaluate the work; the design and statistical choices remain the researchers’ responsibility and are made before STROBE applies.

    Which studies should use STROBE?

    STROBE applies to observational designs, specifically cohort, case-control and cross-sectional studies. Randomised trials, systematic reviews and other study types have their own guidelines, which can be located through the EQUATOR Network’s catalogue.

    How does STROBE relate to reproducibility?

    Complete, transparent reporting is a precondition for reproducibility. By prompting authors to describe data sources, variables, bias and methods fully, STROBE makes it possible for others to appraise, synthesise and attempt to replicate observational findings.

  • Cohort and Case-Control Study Designs

    A cohort study follows groups defined by their exposure forward to see who develops an outcome, while a case-control study starts from the outcome and looks back at exposure. Both are observational designs — the researcher observes rather than assigns exposure — and each answers a question the other cannot answer efficiently.

    This methodology guide explains the two designs, their strengths and weaknesses, and the high-level difference between relative risk and the odds ratio. It is methodological in scope and not medical advice.

    Cohort studies: exposure first, outcome later

    A cohort study groups participants by exposure status and tracks them over time to compare how often the outcome occurs in each group. Two timings exist:

    • Prospective — exposure is recorded now and the cohort is followed forward into the future.
    • Retrospective — the researcher uses existing records to reconstruct exposure in the past and trace outcomes that have already occurred.

    Because exposure is established before the outcome is known, cohort designs are well suited to establishing temporal sequence and to studying multiple outcomes from a single exposure.

    Case-control studies: outcome first, exposure looked back

    A case-control study begins with the outcome: it assembles cases (those with the condition) and controls (comparable individuals without it), then looks back to compare how often each group was exposed. This makes case-control designs efficient for rare outcomes and for situations where a long follow-up would be impractical.

    Side-by-side comparison

    Feature Cohort Case-control
    Starting point Exposure Outcome
    Direction Exposure → outcome Outcome → exposure (look back)
    Good for rare outcomes Inefficient Efficient
    Good for rare exposures Efficient Inefficient
    Multiple outcomes Yes, from one exposure No, single outcome
    Headline measure Relative risk Odds ratio
    Main weakness Cost, loss to follow-up Recall and selection bias

    Relative risk versus odds ratio, conceptually

    The two designs naturally produce different effect measures. A cohort study can compute relative risk — the ratio of the probability of the outcome in the exposed group to that in the unexposed group — because it knows how many people in each group went on to develop the outcome. A case-control study cannot compute that directly, because the researcher chose how many cases and controls to recruit; it instead reports the odds ratio, which compares the odds of exposure between cases and controls. When the outcome is rare, the odds ratio approximates the relative risk closely; as the outcome becomes common, the two diverge. This is a conceptual sketch, not a formula to apply clinically.

    Strengths, weaknesses and bias

    Cohort studies give clear temporal ordering and can study several outcomes, but they are expensive, slow for rare outcomes, and vulnerable to participants dropping out. Case-control studies are quick and efficient for rare outcomes, but are prone to recall bias (cases may remember exposures differently) and to selection bias in how controls are chosen. Neither design assigns exposure, so unmeasured confounding is always a concern — a recurring theme across the research lifecycle.

    STROBE reporting

    Both designs are reported against the STROBE guideline (Strengthening the Reporting of Observational Studies in Epidemiology), a checklist covering how participants were selected, how variables were measured, how bias was addressed and how results were analysed. Transparent reporting lets readers judge validity — the same transparency goal behind structured abstracts, covered in our guide to how to write a research abstract, and the IMRaD structure in the anatomy of a journal article.

    How design choice fits the research record

    Naming a design precisely is part of describing a study well. Controlled terminology in our dictionary and contributor roles via CRediT make that description machine-readable, while our for authors guidance helps report methods clearly.

    Frequently asked questions

    Is a retrospective cohort the same as a case-control study?

    No. A retrospective cohort still groups by exposure and follows toward outcome, using past records; a case-control study groups by outcome and looks back at exposure. The starting point differs.

    Why can’t a case-control study report relative risk?

    Because the researcher sets the number of cases and controls, the underlying population rates of the outcome are unknown, so the odds ratio is used instead.

    Which design is stronger?

    Neither universally. Cohort designs suit common outcomes and temporal questions; case-control designs suit rare outcomes and efficiency. The research question decides.

    What is STROBE for?

    It is a reporting checklist that improves the completeness and transparency of observational studies, helping readers assess potential bias and the strength of the evidence.

  • Reporting guidelines and the EQUATOR Network: CONSORT, PRISMA and beyond

    A study can be impeccably designed and still be impossible to trust, for a simple reason: if the paper does not say what was actually done, no reader can judge whether to believe it, and no one can reproduce it. Under-reporting is one of the quietest threats to reproducibility — not fraud, not bad method, just the omission of the details that would let someone evaluate the work. Reporting guidelines exist to fix this by specifying, item by item, what a paper of a given type must contain. They are a central concern of the reproducibility domain and connect directly to the research-integrity domain, because honest, complete reporting is the precondition for both.

    The EQUATOR Network: a library of guidelines

    The coordinating body for reporting guidelines is the EQUATOR Network — Enhancing the QUAlity and Transparency Of health Research. EQUATOR does not publish a single guideline; it curates and promotes the whole family of them, maintaining a comprehensive online library of reporting guidelines for different study types and providing resources to help authors, editors, and reviewers use them. Its premise is straightforward: there is no point in conducting rigorous research if the publication that reports it omits the information readers need to assess and use it. EQUATOR’s role is to make the right guideline easy to find and to raise the baseline quality of reporting across health research.

    The key thing to understand is that different study designs need different guidelines, because each design has its own ways of being under-reported. A randomised trial can hide how participants were allocated; a systematic review can hide how studies were selected; an animal study can hide how many animals were used and why. A guideline is a checklist tuned to the failure modes of a particular design.

    The major guidelines

    A handful of guidelines account for most everyday use, and it is worth knowing which applies to what.

    • CONSORT (Consolidated Standards of Reporting Trials) is for randomised controlled trials. Its checklist and accompanying flow diagram cover how participants moved through the trial — enrolment, allocation, follow-up, analysis — along with the method of randomisation, blinding, and the pre-specified outcomes. CONSORT is what makes it possible to see whether a trial’s reported result matches the trial it set out to run.
    • PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) is for systematic reviews and meta-analyses. Its checklist and flow diagram document the search strategy, the inclusion and exclusion criteria, and how records were screened and selected. PRISMA is what lets a reader judge whether a review’s conclusions rest on a fair and reproducible survey of the evidence rather than a convenient selection.
    • ARRIVE (Animal Research: Reporting of In Vivo Experiments) is for research involving animals. It sets out the details — species, number and characteristics of animals, housing, the experimental procedures, the statistical methods — needed both to evaluate the work and to honour the ethical principle that animal studies should be reportable and not needlessly repeated.
    • STROBE (Strengthening the Reporting of Observational studies in Epidemiology) is for observational studies — cohort, case-control, and cross-sectional designs — where the reporting challenges differ again from trials.

    These are only the most prominent. EQUATOR’s library extends to qualitative research, diagnostic accuracy studies, case reports, economic evaluations, and many more, with specialised extensions for particular contexts. The skill is in matching the guideline to the study.

    What a guideline actually is — and is not

    It is important to be clear about what reporting guidelines do. A reporting guideline governs how a study is reported, not how it is designed or conducted. CONSORT does not tell you how to run a trial; it tells you what to disclose about the trial you ran. This distinction matters because a guideline cannot rescue a bad study — it can only ensure that a study, good or bad, is described completely enough for readers to tell the difference. Used as a checklist while writing, a guideline prompts authors to include the items that are easy to forget and tempting to omit; used by reviewers and editors, it provides an objective basis for asking “where is the allocation method?” rather than relying on impression.

    Reporting guidelines also pair naturally with the wider machinery of trustworthy research. A CONSORT-compliant trial report is far more valuable when the trial was prospectively registered, so that the pre-specified outcomes in the registration can be checked against those in the paper. A PRISMA-compliant review is stronger when its protocol was registered in advance. The guidelines define completeness of reporting; registration defines commitment in advance; together they close much of the gap between what was planned, what was done, and what was published.

    Practical guidance for authors

    1. Identify the right guideline before you write, not after. Match it to your study design — CONSORT for a trial, PRISMA for a review, ARRIVE for animal work, STROBE for an observational study — using the EQUATOR library to find it.
    2. Use the checklist as you draft, treating each item as a question your paper must answer, and complete the flow diagram where the guideline provides one.
    3. Submit the completed checklist with the manuscript; many journals now require it, and it signals to editors and reviewers that the reporting is complete.
    4. Combine the guideline with registration — register trials and review protocols in advance so that the reported outcomes can be checked against the planned ones.

    Where shared vocabulary fits

    “Reporting guideline”, “checklist”, “flow diagram”, “extension”, and the individual acronyms are used loosely, and confusing a reporting guideline with a study-design standard is a common and consequential error. A shared, federated vocabulary that defines these terms precisely — and points back to the EQUATOR Network and the individual guideline stewards — is what lets a reporting standard cited in one journal be understood the same way in another. Supplying that definitional layer is the role the CASRAI dictionary is designed to play; the relevant terms sit in the reproducibility domain, with adjacent entries in the research-integrity domain.

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