Who is RIGOROUS for?

  • Investigators, for designing, conducting, or reporting studies using routinely collected health data, in academia, industry, government, and third-sector settings.

  • Regulators, HTA bodies, and other evidence users, for assessing whether a study was designed to answer the question it addresses.

  • Editors and peer reviewers, for evaluating whether a study's aims, methods, results, and conclusions are aligned and appropriate.

  • Educators, for teaching structured study design and connecting decisions and principles that are often taught in isolation.

  • Trainees, for planning and reporting research using routinely collected health data.

RIGOROUS

Scope

RIGOROUS has been designed to support quantitative research that uses data generated through routine care and administration rather than for research purposes. This includes primary and secondary care records, prescribing and dispensing data, claims and administrative data, disease registries, and linked resources combining these with cohort or biobank data.

4 Research Tasks

RIGOROUS is explicitly task-based, requiring researchers to first identify the type of question they are asking before proceeding. This is because the task informs everything that follows, including how to formulate a clear research question, the types of biases that might apply, the relevant methods, and the appropriate language for reporting. RIGOROUS covers four tasks: description, signal discovery, prediction, and causal effect estimation, each with its own version of the eight steps.

  • Description

    Estimate the occurrence or distribution of a health state, event, exposure, or practice in a defined population.

  • Signal Discovery

    Scan many exposures, features, drugs, variants, or outcomes to identify candidate signals for further study.

  • Prediction

    Predict current or future outcomes under observed or expected care conditions.

  • Causal Effect Estimation

    Estimate the causal effect of an exposure, treatment, intervention, or policy on an outcome.

The 8 Steps

RIGOROUS is an eight-step framework designed to help researchers improve the quality, transparency, and interpretability of studies using health data.

  • R - Recognize the research task

  • I - Identify estimand(s) and context

  • G - Gauge data fitness

  • O - Outline sources of error and bias

  • R - Run appropriate analyses

  • O - Outline and assess assumptions

  • U - Use appropriate language

  • S - Satisfy reporting and transparency standards

Relationship with Other Guidance

RIGOROUS is distinctive in providing an end-to-end framework for use during the design, conduct, and reporting stages of quantitative health research. It is explicitly task-based and estimand-first, to ensure that researchers fully consider the issues that are relevant to their research question.

RIGOROUS has been designed to complement, not replace, existing guidance and resources. It differs from reporting guidelines such as RECORD and TRIPOD+AI by addressing design and conduct considerations rather than reporting alone. It differs from data quality frameworks by tying data fitness assessment to a specific task and estimand rather than in general terms. And it differs from task-specific methodological frameworks such as target trial emulation, the causal roadmap, and the predictimand framework by integrating insights and conventions from across the broader research space. Where alternative resources provide deeper guidance on a particular step, RIGOROUS explicitly directs users towards them.