Generations of researchers have tested and used attachment theory to understand children's development. To bring coherence to the expansive set of findings from small-sample studies, the field early on adopted meta-analysis. Nevertheless, gaps in understanding intergenerational transmission of individual differences in attachment continue to exist. We discuss how attachment research has been addressing these challenges by collaborating in formulating questions and pooling data and resources for individual-participant-data meta-analyses. The collaborative model means that sharing hard-won and valuable data goes hand in hand with directly and intensively interacting with a large community of researchers in the initiation phase of research, deliberating on and critically reviewing new hypotheses, and providing access to a large, carefully curated pool of data for testing these hypotheses. Challenges in pooling data are also discussed.