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What is Integrative Data Analysis or IDA?  

IDA is a methodology (rather than a single analysis) for the simultaneous analysis of raw data pooled from multiple studies.  The method may be used to examine novel questions in participant-level data (rather than summary statistics from separate studies) and may accomodate some degree of measurement differences across pooled studies. The method describes a multi-staged approach to addressing issues within any pooled data application for item-level harmonization, psychometric analyses to create commensurate measures across studies, testing hypotheses with pooled data, and examining reproducibility or study differences.

What are potential advantages of pooled data analysis?What are unique features of IDA?What makes IDA different than traditional Meta-Analysis?
Larger sample sizes & increased statistical powerPooling at the individual participant rather than pooled study level of analysisAnalysis of individual participant data rather than summary statistics
Greater sample heterogeneity to test generalizabilityUse of psychometric models for scoringDesigned to answer novel questions not addressed in prior analyses
Ability to test cross-study replication and reproducibilityConsideration of study differences in hypothesis testingGreater power for studying individual differences