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…

The intent of this paper is to demonstrate that the standard age effect in analysis of variance provides an ineffective means of assessing developmental change when several age levels are involved and a roughly monotonic trend can be expected. (Author)

Lists three criteria that can codetermine whether a new methodological technique is embraced by developmental researchers. Criteria include theoretical and methodological zeitgeist, conceptual and functional accessibility, and perspective enhancement. Using these criteria, evaluates the potential impact of structural equation modeling. (Author/RH)

Identifies interaction effects as the defining feature of resilience and resilience research. Maintains that interaction effects are responsible for the unique contributions of this field of study to the understanding of human development. Suggests that the methodological and statistical challenges posed by interaction effects do not, by…

Examines the manner in which the data-driven character of child development research limits the validity and penetration of the search for new knowledge and understanding, and imposes a skewed image of what is known about children and childhood by excluding the less objective observations and insights of the clinicians and practitioners.…

Responds to Herbert Zimiles's criticisms in this issue of an overreliance on empirical, quantitative data in child development research, arguing that, although quantitative research has limitations, intuition is no substitute for a rigorous, systematic investigation of a hypothesis. (MDM)

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)

Responds to commentaries in this issue by Greta Fein and by Daniel Walsh and Gary King on criticisms of quantitative research. Argues that the data-driven nature of child development research has an impact not only on how research questions are answered but on what questions are asked in the first place. (MDM)

Illustrates problems facing researchers trying to demonstrate causal relationships between types of nonparental care and differences between groups of Swedish children. Argues that efforts must be made to validate and interpret differences that are found. Indicates ways to avoid misinterpretation of differences that are attributable to…