Latent class/profile analysis in maltreatment research: a commentary on Nooner et al., Pears et al., and looking beyond.

Latent class (LCA) and latent profile (LPA; also referred to as continuous LCA) analyses are person-centered statistical techniques that allow researchers to assign individuals to one mutually exclusive class (or profile) based on their responses to observed variables of interest (e.g., maltreatment types). Resultant classes are then substantively characterized by interpreting common patterns of responses within and between the classes/profiles. These techniques, part of a broader class of statistical models referred to as finite mixture models (see McLachlan & Peel, 2000), allow researchers to identify typologies of people rather than a taxonomy of variables as is customary in research using exploratory or confirmatory factor analysis. The LCA of Nooner et al. (2010) and the LPA of Pears, Kim, and Fisher (2008) both display the usefulness of these techniques with maltreatment data. Moreover, they have extended the limited number of LCA/LPA studies in the maltreatment field (e.g., Romano, Zoccolillo, & Paquette, 2006) by identifying multidimensional class/profile solutions that are more sophisticated than no maltreatment class/profile and a at least one type of maltreatment class/profile. The primary goal of this commentary is to provide a brief, user-friendly approach to conducting LCA/LPA. To that end, we (1) conceptually describe the goals of LCA/LPA, (2) highlight decision-making rules and practical issues of primary importance when applying LCA/LPA, and (3) identify newapplications of finitemixturemodels as they could potentially be applied inmaltreatment research. Throughout this commentary we critique both the Nooner et al. and Pears et al. studies. While the use of LCA/LPA has increased in recent years with child and adolescent samples (see examples of uses below), the application of this technique has been slower in maltreatment research (however, see McCrae, Chapman, & Christ, 2006; Romano et al., 2006). LCA has been applied to a variety of research designs in the social and behavioral sciences. For example, LCA has been used to identify patterns of co-occurrences for general problem behaviors during adolescence (Fergusson, Horwood, & Lynskey, 1994; Thompson, Brownfield, & Sorenson, 1998), child academic, social, and behavior problems (Reinke, Herman, Petras, & Ialongo, 2008; Tolan & Henry, 1996), temperament, interaction styles, and peer play in infants and toddlers using observational data (Loken, 2004;Webels & von Eye, 1996), and delinquent behaviors among adolescents (D’Unger, Land, MOdgers et al., 2007).Moreover, LCAhas beenused to identify patterns of comorbidity for psychiatric symptoms of affective disorders (Ferdinand, Bongers, et al., 2006; Ferdinand, de Nijs, van Lier, & Verhulst, 2005; Ferdinand, van Lang, Ormel, Verhulst, 2006; van Lang, Ferdinand, Ormel, & Verhulst, 2006; Wadsworth, Hudziak, Heath, & Achenbach, 2001), conduct disorder (Nock, Kazdin, Hirip, & Kessler, 2006) attention-deficit/hyperactivity disorder (ADHD; Althoff, Copeland, et al., 2006; de Nijs, Ferdinand, & Verhulst, 2007; Neumann et al., 1999), ADHDwith other psychiatric disorders (Acosta et al., 2008; Volk, Neuman, & Todd, 2005), disruptive behavior disorders (de Nijs, van Lier, Verhulst, 2007; Sondeijker et al., 2005; Storr, Accornero, & Crum, 2007; van Lier, Verhulst, van der Ende, & Crijnen, 2003), hallucinogen dependence syndromes (Stone, Storr, & Anthony, 2006), and nonverbal learning disabilities (Ris et al., 2007). In addition to the identification of patterns of behaviors and psychiatric symptoms and disorders, LCA has been applied in the examination of the co-occurrence of aspects of the social environment. For example, LCA has been used to identify patterns of environmental risk and protective factors for academic, psychological, and behavior problems (Bowen, Lee, & Weller, 2007; Walrath et al., 2004), adverse life experiences (Shevlin & Elklit, 2008), and peer victimization (Nylund,