Developmental science rests on describing, explaining, and optimizing intraindividual changes and, hence, empirically requires longitudinal research. Problems of missing data arise in most longitudinal studies, thus creating challenges for interpreting the substance and structure of intraindividual change. Using a sample of reports of longitudinal…

To avoid reduction in observational data resulting from correlational techniques for analyzing interpersonal interactions, a data-transformation method based on multidimensional scaling techniques was applied to the Family Interaction Coding System. Two resulting dimensions, prosocial-deviance and high-low involvement, were applied to observations…

Two ways of studying lives in context through time are analysis of longitudinal data and secondary data analysis of long-term studies intended to answer questions not originally posed. The opportunities for, and limitations of, these types of analysis; their relevance to policy; and their applicability to interdisciplinary research are considered.…

Discusses procedures and considerations involved with secondary analyses of longitudinal databases. Procedures involve (1) formulating questions; (2) creating a feasibility matrix; (3) reformulating questions; (4) creating derived variables; (5) performing data reduction; (6) analyzing data; and (7) interpreting results. Problems associated with…

This article provides a history of the data set known as "the Children of the National Longitudinal Survey of Youth (NLSY)." Promising research agendas that use the data set are described. These agendas concern maternal employment and child care, adolescent pregnancy and parenthood, divorce, poverty, and multigenerational parenting. (BC)