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Quality Assessment in Meta-Analyses (QuAMA)
Scherer, Ronny; Emslander, Valentin
2022
 

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Keywords :
Meta-analysis; Structural equation modeling; Composite variable; Moderator analysis; Quality assessment; Latent variables
Abstract :
[en] This project develops methods and procedures to (a) quantify the quality of primary studies in meta-analyses; and (b) account for primary-study quality in moderator analyses. As part of the project, we develop an analytic procedure to create study quality indicators and incorporate them in the meta-analysis. We will present this procedure in a step-by-step tutorial with illustrative examples.
Research center :
- Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Luxembourg Centre for Educational Testing (LUCET)
Disciplines :
Mathematics
Theoretical & cognitive psychology
Author, co-author :
Scherer, Ronny;  University of Oslo, Norway > Faculty of Educational Sciences > Centre for Educational Measurement at the University of Oslo (CEMO)
Emslander, Valentin  ;  University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > LUCET
Language :
English
Title :
Quality Assessment in Meta-Analyses (QuAMA)
Publication date :
03 August 2022
Focus Area :
Educational Sciences
Computational Sciences
Additional URL :
Name of the research project :
QuAMA
Commentary :
Research Questions Which analytic steps and methodological decisions are relevant for the creation of quality indicators or primary studies in meta-analyses? How can these indicators be incorporated in meta-analytic models? Hypotheses We hypothesize that the following steps and issues will be relevant: (a) the level at which quality is measured and the resultant type of quality that is measured; (b) the directions and correlations of quality indicators; (c) the assumptions behind aggregated quality scores; (d) the nature and scales of indicators; (e) the choice for an adequate, meta-analytic baseline model; (f) the study of possible non-linear effects. We expect the following meta-analytic steps to gain insights into the effects of study quality: (1) Moderation by study quality; (2) Moderation after controlling for study quality; (3) Moderation including interactions with study quality. Data Description In our illustrative examples, we will use one or more existing, meta-analytic datasets: (a) Scherer et al. (2019), https://doi.org/10.1037/edu0000314 (b) Scherer et al. (2021), https://doi.org/10.31234/osf.io/bucf9 (c) Datasets published in the R package "metadat" (by Wolfgang Viechtbauer), https://cran.r-project.org/web/packages/metadat/readme/README.html (d) Emslander & Scherer (2022), https://doi.org/10.17605/OSF.IO/VN5PE
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since 17 August 2022

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