Taxometrics and Criminal Justice: Assessing the Latent Structure of Crime-Related Constructs

Abstract

PurposeThe taxometric method is introduced as a way of investigating the latent structure of key criminal justice constructs. MethodsBesides describing the theory, rationale, and procedures behind taxometrics, the taxometric method is applied to Wolfgang, Figlio, and Sellin’s (1972) delinquency cohort data to illustrate how the procedure works. ResultsAfter defining latent structure, its relevance to criminal justice is explored and the four core principles of taxometric analysis are described: coherent cut kinetics, consistency testing, comparison curve analysis, and evidence-based procedures. Sample and indicator preconditions for taxometric analysis are discussed and empirically-verified procedures for taxometric analysis are outlined: mean above minus below a cut (MAMBAC: Meehl & Yonce, 1996), maximum covariance (MAXCOV: Meehl & Yonce, 1994), maximum eigenvalue (MAXEIG: Waller & Meehl, 1998), maximum slope (MAXSLOPE: Grove & Meehl, 1993), and latent mode factor analysis (L-Mode: Waller & Meehl, 1998). ConclusionsThe taxometric method provides an avenue by which the latent structure of important criminal justice constructs can be explored and criminal justice research can be advanced.