Statistical Methods for Describing Developmental Patterns

Abstract

Identification of effective practices in the care and education of young children is a major goal for professionals and parents. While extensive research has been conducted to address this broad goal, relatively few studies have been able to document children's and families' development over time and identify processes underlying those developmental patterns. Briefly described here are a wide variety of analytic tools available to address questions about development. Growth curve methods provide descriptions of individual and group patterns of change and can identify factors associated with those developmental patterns when longitudinal data are collected. Hierarchical regressions or path analyses can test hypotheses based on ecological models by using the approach suggested by Baron and Kenny (1986) to identify mediators and moderators of development. Both primary and secondary data analysis of project and extant data can provide insights into factors related to development, especially those related to how risk and protective factors mediate or moderate patterns of development. While many of these methods are not easy to implement, their judicious use should enhance our knowledge about early learning and development. An example of a secondary analysis of cognitive development among children in two early intervention projects is presented to demonstrate some of these techniques.