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Identifying and understanding causal risk factors for crime over the life-course is a key area of inquiry in developmental criminology. Prospective longitudinal studies provide valuable information about the relationships between risk factors and later criminal offending. Meta-analyses that synthesize findings from these studies can summarize the predictive strength of different risk factors for crime, and offer unique opportunities for examining the developmental variability of risk factors. Complex data structures are common in such meta-analyses, whereby primary studies provide multiple (dependent) effect sizes.

This paper describes a recent innovative method for handling complex meta-analytic data structures arising due to dependent effect sizes: robust variance estimation (RVE). We first present a brief overview of the RVE method …