Avoiding Methodological Biases in Meta-Analysis: Use of Online Versus Offline Individual Participant Data (IPD) in Educational Psychology
Individual participant data (IPD) meta-analysis is the gold standard of meta-analyses. This paper points out several advantages of IPD meta-analysis over classical meta-analysis, such as avoiding aggregation bias (e.g., ecological fallacy or Simpson's paradox) and shows how its two main disadva...
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Veröffentlicht in: | Zeitschrift für Psychologie 2016-01, Vol.224 (3), p.157-167 |
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Sprache: | eng |
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Zusammenfassung: | Individual participant data (IPD) meta-analysis is the
gold standard of meta-analyses. This paper points out several advantages of IPD
meta-analysis over classical meta-analysis, such as avoiding aggregation bias
(e.g., ecological fallacy or Simpson's paradox) and shows how its two
main disadvantages (time and cost) can be overcome through Internet-based
research. Ideally, we recommend carrying out IPD meta-analyses that consider
online versus offline data gathering processes and examine data quality. Through
a comprehensive literature search, we investigated whether IPD meta-analyses
published in the field of educational psychology already follow these
recommendations; this was not the case. For this reason, the paper demonstrates
characteristics of ideal meta-analysis on teachers' judgment accuracy and
links it to recent meta-analyses on that topic. The recommendations are
important for meta-analysis researchers and for readers and reviewers of
meta-analyses. Our paper is also relevant to current discussions within the
psychological community on study replication. |
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ISSN: | 2190-8370 2151-2604 |
DOI: | 10.1027/2151-2604/a000251 |