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Comparing Meta‐analysis and Individual Person Data Analysis Using Raw Data on Children's Understanding of Equivalence
Author(s) -
Hornburg Caroline Byrd,
Wang Lijuan,
McNeil Nicole M.
Publication year - 2018
Publication title -
child development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.103
H-Index - 257
eISSN - 1467-8624
pISSN - 0009-3920
DOI - 10.1111/cdev.13058
Subject(s) - meta analysis , moderation , raw data , psychology , equivalence (formal languages) , raw score , regression analysis , meta regression , estimation , statistics , developmental psychology , cognitive psychology , social psychology , mathematics , medicine , management , economics , discrete mathematics
A prevailing theory of mathematical problem solving predicts that children will be less accurate solving a + b = c + __ problems versus a + b = __ + c . However, this has never been tested directly. Because of low base rates, information combined from multiple studies can help improve estimation accuracy and precision. This study compared meta‐analysis and individual person data (IPD) analysis using raw data from 14 studies ( N = 1,414; n s = 30–232; M age reported = 8;7). Substantive results challenge the prevailing theory. Methodological results demonstrate the advantages of using meta‐analysis and IPD over single‐study analysis. Moreover, IPD can be more powerful than meta‐regression for detecting between‐study moderation effects.