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…

Existing data sets can be an efficient, powerful, and readily available resource for addressing questions about developmental science. Many of the available databases contain hundreds of variables of interest to developmental psychologists, track participants longitudinally, and have representative samples. In this article, the authors discuss the…

Data collection can be the most time- and cost-intensive part of developmental research. This article describes some long-proposed but little-used research designs that have the potential to maximize data quality (reliability and validity) while minimizing research cost. In "planned missing data designs", missing data are used…

In a series of four experiments, the authors begin by replicating Flavell, Shipstead, and Croft's (1980) finding that many children between 2 and 4 years of age will affirm the invisibility both of themselves and of others--but "not" of the body--when the person's eyes are closed. The authors also render explicit certain trends in the Flavell et…

Longitudinal data analysis has long played a significant role in empirical research within the developmental sciences. The past decade has given rise to a host of new and exciting analytic methods for studying between-person differences in within-person change. These methods are broadly organized under the term "growth curve models." The…