TY  - JOUR
A1  - Brunner, Martin
A1  - Keller, Lena
A1  - Stallasch, Sophie E.
A1  - Kretschmann, Julia
A1  - Hasl, Andrea
A1  - Preckel, Franzis
A1  - Luedtke, Oliver
A1  - Hedges, Larry
T1  - Meta-analyzing individual participant data from studies with complex survey designs
BT  - a tutorial on using the two-stage approach for data from educational large-scale assessments
JF  - Research synthesis methods
N2  - Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. 
Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational large-scale assessments (ELSAs) or social, health, and economic survey and panel studies. The meta-analytic integration of these results offers unique and novel research opportunities to provide strong empirical evidence of the consistency and generalizability of important phenomena and trends. 

Using ELSAs as an example, this tutorial offers methodological guidance on how to use the two-stage approach to IPD meta-analysis to account for the statistical challenges of complex survey designs (e.g., sampling weights, clustered and missing IPD), first, to conduct descriptive analyses (Stage 1), and second, to integrate results with three-level meta-analytic and meta-regression models to take into account dependencies among effect sizes (Stage 2). 

The two-stage approach is illustrated with IPD on reading achievement from the Programme for International Student Assessment (PISA). We demonstrate how to analyze and integrate standardized mean differences (e.g., gender differences), correlations (e.g., with students' socioeconomic status [SES]), and interactions between individual characteristics at the participant level (e.g., the interaction between gender and SES) across several PISA cycles. 

All the datafiles and R scripts we used are available online. Because complex social, health, or economic survey and panel studies share many methodological features with ELSAs, the guidance offered in this tutorial is also helpful for synthesizing research evidence from these studies.
KW  - complex survey designs
KW  - educational large-scale assessments
KW  - individual
KW  - participant data
KW  - meta-analysis
KW  - Programme for International Student
KW  - Assessment
Y1  - 2022
U6  - https://doi.org/10.1002/jrsm.1584
SN  - 1759-2879
SN  - 1759-2887
VL  - 14
IS  - 1
SP  - 5
EP  - 35
PB  - Wiley
CY  - Hoboken
ER  -