Estimating Relative Stability in Developmental Research: A Critique of Modern Approaches and a Novel Method

• NCJ Number: 251828
• Journal: Journal of Quantitative Criminology Volume: 33 Issue: 2 Dated: June 2017 Pages: 319-346
• Author(s): J.C. Barnes; Sarah A. El Sayed; Michael TenEyck; Joseph L. Nedelec; Eric J. Connolly; Joseph A. Schwartz; Brian B. Boutwell; John P. Wright; Kevin M. Beaver; Nathaniel E. Anderson
• Date Published: June 2017
• Length: 28 pages
• Grant Number(s): 2007-MU-FX-0002
• Sponsoring Agency: Office of Juvenile Justice and Delinquency Prevention (OJJDP)
• Publication Format: Article; Document; Document (Online)
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description
• Language: English
• Country: United States of America

Annotation

This study drew on data from the Pathways to Desistance study in examining whether the methods typically used to analyze longitudinal development provide a parameter estimate for relative stability.

Abstract

Developmental/life-course (DLC) criminologists often study the age-graded trajectories of traits and behaviors known to correlate with antisocial outcomes. Much of this work has attempted to discern whether traits like impulse control are relatively stable across different portions of the life course. A range of statistical techniques have been used by researchers in attempting to parameterize relative stability. Yet, despite these attempts, much of the evidence remains mixed. The results of the current study indicate that none of the methods typically used by DLC researchers provide a parameter estimate for relative stability. In order to address this oversight, this study developed a novel method called P(Delta) that can be used to estimate the amount of relative (in)stability that is observed in a longitudinal dataset. Although P(Delta) provides a direct estimate of the degree to which relative (in)stability is observed in one's dataset, there are several important points that must be considered by future DLC researchers in order to further develop P(Delta) into a statistic that can be used for inferential analysis. These points are discussed in this article. (Publisher abstract modified)