Importantly, IDA also permits tests of hypotheses that have not or sometimes cannot be tested within a single contributing study (e.g., due to the greater age heterogeneity in the pooled sample created by combining longitudinal studies to cover a broader swath of the lifespan) and directly evaluates replication of hypothesis tests across contributing studies. Unlike other approaches to research synthesis that are based on summary statistics, IDA may be used to test even complex associations among variables (e.g., moderation and mediation) that were not previously tested in contributing studies, providing a means for accelerating the pace of novel hypothesis testing. By accounting for potential between-study sources of heterogeneity, IDA also permits tests of whether these associations differ in magnitude or form over study, a direct evaluation of replication across the pooled studies. Depending on the application, this approach may be extended to explicitly model factors that may account for between study differences in findings, with potential factors spanning multiple levels of design such as study differences in sampling, geographic region, history, and assessment protocol. Thus, IDA permits an exploration of
