Amid recent progress in cognitive development research, high-quality data resources are accumulating, and data sharing and secondary data analysis are becoming increasingly valuable tools. Integrative data analysis (IDA) is an exciting analytical framework that can enhance secondary data analysis in powerful ways. IDA pools item-level data across multiple studies to make inferences possible both within and across studies and can be used to test questions not possible in individual contributing studies. Some of the potential benefits of IDA include the ability to study longer developmental periods, examine how the measurement of key constructs changes over time, increase subject heterogeneity, and improve statistical power and capability to study rare behaviors. Our goal in this article is to provide a brief overview of the benefits and challenges of IDA in developmental research and to identify additional resources that provide more detailed discussions of this topic.
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Developmental and Educational Psychology
- Psychiatry and Mental health