Browsing by Subject "Latent class analysis"
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Item A Latent Class Analysis of Psychopathy Subtypes in a Sex Offender Population(2017-06-05) McCallum, Katherine E.; Boccaccini, Marcus T.Past research has provided evidence for primary and secondary subtypes of psychopathy. Research in this area has focused on broad male offender samples, though some studies have investigated more specific populations such as college students, juvenile offenders, and African American male offenders. No studies have investigated primary and secondary psychopathy in sex offender populations. Psychopathy is an integral construct in sexually violent predator evaluations. Some studies have investigated subtypes of sex offenders and interesting parallels are apparent between these findings and primary and secondary subtypes of psychopathy. Yet, no prior studies have attempted to merge these seemingly parallel lines of research. This study addresses this gap by examining whether there is support for primary and secondary psychopathy among a sample of sex offenders. Specifically, this study used a latent class analysis (LCA) approach to analyze scores on the Psychopathy Checklist-Revised (PCL-R) and Personality Assessment Inventory (PAI) profiles from 487 offenders evaluated for post-release civil commitment. The results of this study describe latent subtypes of psychopathy within this sample, as well as additional latent subtypes with low levels of psychopathy, allowing for comparison with previous sex offender subtype studies.Item Investigating factor structure of scores on the outcome questionnaire using factor mixture modeling(2009-08) Kim, Seong-Hyeon; Sherry, Alissa René; Beretvas, Susan NatashaThe Outcome Questionnaire (OQ-45; Lambert et al., 1996) has been widely employed as a psychotherapy outcome monitoring measure following research findings that support various aspects of its validity and sensitivity to change. Despite its broad usage in both clinical and research settings, some of its psychometric properties are not definite. The three subscales of the OQ-45 are designed to measure three distinct, but related, aspects of psychological functioning. However, neither the one- nor three-factor models have been supported by previous research. Likewise, the results of the current study supported neither of those factor structures. It was suspected that heterogeneity in data might have led to the lack of the confirmatory factor analysis model fit. Therefore, factor mixture modeling (FMM), a combination of confirmatory factor analysis and latent class analysis, was employed to investigate potential heterogeneity of the data. Among the series of factor mixture models with varying numbers of classes that were fitted, the two-class, unconditional FMM based on the revised three-factor solution was decided to best describe the data under analysis. Although three covariates of clinical status, sex, and race were selected as known sources of heterogeneity and incorporated into the FMMs (i.e., conditional model), the findings were contradictory to expectations. The implications of these findings in counseling were discussed in terms of aggregating OQ-45 scores and its score interpretation. Furthermore, this study demonstrates the process involved and dilemmas encountered in choosing the best fitting FMM. There is currently no criterion for assessing individual model fit. Instead, models’ fit are compared using various information criteria (IC). And, as was found in the current study, these ICs are frequently contradictory. Thus, the process of identifying the best fitting model cannot rest solely on fit indices but must also depend on interpretation of models and consideration of the ultimate use of the results. In the current study, consideration of transition matrices and the pattern of latent means across classes contributed as much to model selection as fit index interpretation.Item The patchwork perspective : multi-informant ratings of children’s psycho-social well-being over time using child and informant factors(2011-05) Silcox, Karen Kinsel, 1975-; Anderson, Edward Robert; Huston, Aletha; Kim, Su Yeong; Hazen-Swann, Nancy; Loukas, AlexandraThis study was part of a larger multi-informant longitudinal study with a sample of 319 children (52% male, 48% female) ages 4-12 (mean= 7 years 9 months) whose parents had recently filed for divorce. Three annual waves of data from four informants were used for analysis: child self-report, mother, teacher, and observer report. The purpose of the study was to add to the understanding of multi-informant research and children’s psycho-social well-being. The first goal was to determine the consensus of children’s psycho-social well-being scores within informant across time, within child across informant, and between children over time. The second goal was to determine factors that contribute to the levels of consensus, such as, child gender, child age, child ethnicity, and length of parents’ separation, maternal baseline depressive symptoms score, and timing of the teacher questionnaire. The third goal was to determine if children could be classified into meaningful psycho-social well-being groups. Lastly, a visual diagnostic tool, the “patchwork”, was created using a random sample of eight prototypical cases of group membership based on predicted probabilities. This tool displayed the four informants scores, and child and informant characteristics. A single measure of child psycho-social well-being was created for each informant to compare rater consensus in hierarchical linear modeling. Latent class analysis was used to determine groupings. The HLM results indicate that 53% of the variance is within informants across time, 31% is within child across raters, and only 16% is between child over time. As expected, results showed more consensus of informants’ scores among girls than boys, the greatest consensus for children in middle childhood over other age groups, among Non-Hispanic White children compared to other ethnicities, and among spring reports than fall reports from teachers. Maternal baseline depressive symptoms score was significantly related to level of consensus of reporters, with greatest consensus when mother’s baseline depressive symptoms scores are at the mean (15.47). Mother’s scores of children’s psycho-social well-being decrease from highest scores of when baseline depressive symptoms score is 0, decreasing -.02 with each point increase in baseline depressive symptoms score. The results of the latent class analysis show two latent classes with maternal baseline depressive symptoms as a covariate best fit the data, one class with psycho-social well-being scores above the mean (N=258), and one with scores below the mean (N=61). Baseline data alone sufficiently models these groups and is chosen for parsimony over latent transition analysis. In sum, this study demonstrated benefits of multi-method multi-informant research, while acknowledging the strengths and biases that influence informant consensus of children’s psycho-social well being