Meta-analyses of partial correlations are biased: Detection and solutions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F24%3A10486014" target="_blank" >RIV/00216208:11230/24:10486014 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=OWJtDybQOZ" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=OWJtDybQOZ</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1002/jrsm.1704" target="_blank" >10.1002/jrsm.1704</a>
Alternative languages
Result language
angličtina
Original language name
Meta-analyses of partial correlations are biased: Detection and solutions
Original language description
We demonstrate that all meta-analyses of partial correlations are biased, and yet hundreds of meta-analyses of partial correlation coefficients (PCCs) are conducted each year widely across economics, business, education, psychology, and medical research. To address these biases, we offer a new weighted average, UWLS+3. UWLS+3 is the unrestricted weighted least squares weighted average that makes an adjustment to the degrees of freedom that are used to calculate partial correlations and, by doing so, renders trivial any remaining meta-analysis bias. Our simulations also reveal that these meta-analysis biases are small-sample biases (n < 200), and a simple correction factor of (n - 2)/(n - 1) greatly reduces these small-sample biases along with Fisher's z. In many applications where primary studies typically have hundreds or more observations, partial correlations can be meta-analyzed in standard ways with only negligible bias. However, in other fields in the social and the medical sciences that are dominated by small samples, these meta-analysis biases are easily avoidable by our proposed methods.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50201 - Economic Theory
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Research Synthesis Methods
ISSN
1759-2879
e-ISSN
1759-2887
Volume of the periodical
15
Issue of the periodical within the volume
2
Country of publishing house
GB - UNITED KINGDOM
Number of pages
13
Pages from-to
313-325
UT code for WoS article
001160973500001
EID of the result in the Scopus database
2-s2.0-85185150425