Qualitative Rigor & COREQ Auditor
Audits your rigor strategies against COREQ
Qualitative Rigor & COREQ Auditor
Audits your rigor strategies against COREQ
Description
Writes a Methods section based on Lincoln & Guba's trustworthiness criteria from your qualitative study design; then reveals which COREQ checklist items are missing or weakly reported, without concealment. Who it's for: researchers seeking reporting robustness before journal submission and graduate students writing a thesis.
Recommended by
Shuting@YouMind
Why we love this skill
An editor-level audit that turns your documented qualitative procedures into a trustworthiness-focused Methods section, then tests every reporting detail against COREQ’s 32 items. It is especially valuable for exposing missing reflexivity and rigor evidence without inventing strategies or overstating compliance.
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Related Skills
View allSTROBE/CONSORT Methods-Results Writer
Produces a complete Methods + Results section following the reporting standard that fits your study design (STROBE for observational studies, CONSORT for randomized controlled trials); then audits which checklist items are missing or weakly reported without concealment, and suggests how to complete them. Who it's for: researchers seeking reporting robustness before journal submission and graduate students writing a thesis.
STROBE Methods Writer
Based on your cross-sectional, cohort, or case-control study design; when you enter your participant selection method, variables, sample size rationale, and statistical methods, it produces a complete Methods and Results draft with implicit reference to all 22 items of the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. It also provides a mapping table at the end showing which paragraph corresponds to which STROBE item — ready to answer a journal's "please complete the STROBE checklist" request. Avoids causal language (uses "is associated with" rather than "causes" for observational studies) and explicitly discusses sources of bias/confounding. Suitable for academics working in epidemiology, public health, and clinical research.
Statistical Report + Reviewer Objection
Produces a complete Results section from your descriptive + inferential statistics outputs (including assumption tests). If it detects a normality or variance homogeneity violation, it recommends the non-parametric alternative test rather than concealing it. It also pre-identifies at least 4 objections journal reviewers commonly raise (e.g., "assumption tests not reported", "effect size not stated", "no multiple comparison correction applied") and provides a defense sentence for each. Who it's for: researchers working with quantitative methods who want statistical reporting rigor before journal submission.
