2021
DOI: 10.1002/jrsm.1487
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Improving the reporting quality of reliability generalization meta‐analyses: The REGEMA checklist

Abstract: Reliability generalization (RG) is a meta‐analytic approach that aims to characterize how reliability estimates from the same test vary across different applications of the instrument. With this purpose RG meta‐analyses typically focus on a particular test and intend to obtain an overall reliability of test scores and to investigate how the composition and variability of the samples affect reliability. Although several guidelines have been proposed in the meta‐analytic literature to help authors improve the re… Show more

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Cited by 65 publications
(43 citation statements)
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“…Use well-established, up-to-date reporting guidelines intended for meta-analyses such as: the recently updated PRISMA 2020 (Page et al, 2021); the focused-on reliability generalization meta-analyses REGEMA (Sánchez-Meca et al, 2021); the focused-on non-intervention studies NIRO-SR (Topor et al, 2020), for example.…”
Section: Discussionmentioning
confidence: 99%
“…Use well-established, up-to-date reporting guidelines intended for meta-analyses such as: the recently updated PRISMA 2020 (Page et al, 2021); the focused-on reliability generalization meta-analyses REGEMA (Sánchez-Meca et al, 2021); the focused-on non-intervention studies NIRO-SR (Topor et al, 2020), for example.…”
Section: Discussionmentioning
confidence: 99%
“…This RG study was reported following the Guidelines for conducting and reporting reliability generalization meta-analyses (REGEMA; Sánchez-Meca et al., 2021 ). Appendix A includes the REGEMA checklist for the present meta-analysis.…”
Section: Methodsmentioning
confidence: 99%
“…First, a systematic review was carried out following the PRISMA methodology (Urrútia and Bonfill, 2010). A meta-analysis was then carried out following the recommendations of the REGEMA guidelines (Sánchez-Meca et al, 2021). We also followed specific guidelines for performing reliability generalization meta-analyses (Sánchez-Meca et al, 2009;Rubio-Aparicio et al, 2018).…”
Section: Methodsmentioning
confidence: 99%