The Experts below are selected from a list of 29748 Experts worldwide ranked by ideXlab platform
James J Hudziak - One of the best experts on this subject based on the ideXlab platform.
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Latent Class Analysis of the child behavior checklist obsessive compulsive scale
Comprehensive Psychiatry, 2009Co-Authors: Robert R Althoff, James J Hudziak, David C Rettew, Dorret I BoomsmaAbstract:The Obsessive-Compulsive Scale (OCS) of the Child Behavior Checklist (CBCL) predicts obsessive-compulsive disorder and is highly heritable. Latent Class Analysis (LCA) of the OCS was used to identify profiles within this 8-item scale and to examine heritability of those profiles. The LCAwas performed on maternal CBCL reports of their 6- to 18-year–old children from 2 US nationally representative samples from 1989 (n = 2475, 50% male) and 1999 (n = 2029, 53% male) and from Dutch twins in the Netherlands Twin Registry at ages 7 (n = 10 194, 49.3% male), 10 (n = 6448, 48.1% male), and 12 (n = 3674, 48.6% male) years. The heritability of the resultant Classes was estimated using odds ratios of twin membership across Classes. A 4-Class solution fitted all samples best. The resulting Classes were a “No or Few Symptoms” Class, a “Worries and Has to Be Perfect” Class, a “Thought Problems” Class, and an “OCS” Class. Within-Class odds ratios were higher than across-Class odds ratios and were higher for monozygotic than dizygotic twins. We conclude that LCA identifies an OCS Class and that Class is highly heritable using across-twin comparisons.
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Latent Class Analysis of child behavior checklist anxiety depression in children and adolescents
Journal of the American Academy of Child and Adolescent Psychiatry, 2001Co-Authors: Martha E Wadsworth, James J Hudziak, Andrew C Heath, Thomas M AchenbachAbstract:ABSTRACT Objective Comorbidity of psychiatric problems such as anxiety and depression poses challenges to treatment and research. This study tested whether problem items from the Anxious/Depressed scale of the Child Behavior Checklist (CBCL) can be separated into distinct anxiety and depression Classes or are continuously distributed throughout a population. Method A CBCL was completed by a parent or guardian of each of 1,987 children and adolescents selected to represent nonreferred children in the United States, as well as by a parent or guardian of each of a demographically matched sample of 1,987 clinically referred children and adolescents. Problem items from the Anxious/Depressed scale of the CBCL were subjected to Latent Class Analysis. Results Analyses revealed three levels of problem presentation in both samples. Children in the nonreferred sample were Classified as having no problems, mild problems, or moderate anxiety/depression problems. Children and adolescents in the referred group were Classified as having mild, moderate, or severe levels of problems. No pure anxiety or depression Classes were found, only Classes containing a mixture of both anxiety and depressive problems. Age, gender, and sample differences were found in Class groupings, with nonreferred adolescent girls showing elevated levels of problems. Conclusions Results suggest that the comorbid conditions of anxiety and depression, as assessed by the CBCL anxiety/depression problem items, can be thought of as part of the same continuum of problems. Implications for assessment and treatment utilization are discussed.
James K Hammitt - One of the best experts on this subject based on the ideXlab platform.
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peeling back the onion using Latent Class Analysis to uncover heterogeneous responses to stated preference surveys
Journal of Environmental Economics and Management, 2018Co-Authors: James K Hammitt, Daniel HerreraaraujoAbstract:Abstract We develop validity tests for application to stated-preference estimates of WTP to reduce mortality risk, i.e., value per statistical life (VSL), and apply these to data obtained by surveying a representative sample of French adults over the internet. These tests (WTP nearly proportional to risk reduction, insensitive to small differences in baseline risk, increasing in income, and consistent with budget constraints) are satisfied by a conventional single-regression Analysis of our data. Using Latent Class Analysis (LCA), we identify important differences between respondents in their consistency with the validity tests and control for much of this heterogeneity. Estimates of VSL from the Latent Class that is consistent with the validity tests are smaller than estimates from the standard Analysis. We estimate mean VSL for adults of about 2 million € and for children (based on parents' WTP) of about 6 million €.
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peeling back the onion using Latent Class Analysis to uncover heterogeneous responses to stated preference surveys
Post-Print, 2017Co-Authors: James K Hammitt, Daniel HerreraaraujoAbstract:We develop validity tests for application to stated-preference estimates of WTP to reduce mortality risk, i.e., value per statistical life (VSL), and apply these to data obtained by surveying a representative sample of French adults over the internet. These tests (WTP nearly proportional to risk reduction, insensitive to small differences in baseline risk, increasing in income, and consistent with budget constraints) are satisfied by a conventional single-regression Analysis of our data. Using Latent Class Analysis (LCA), we identify important differences between respondents in their consistency with the validity tests and control for much of this heterogeneity. Estimates of VSL from the Latent Class that is consistent with the validity tests are smaller than estimates from the standard Analysis. We estimate mean VSL for adults of about 2 million e and for children (based on parents’ WTP) of about 6 million euros.
Daniel Herreraaraujo - One of the best experts on this subject based on the ideXlab platform.
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peeling back the onion using Latent Class Analysis to uncover heterogeneous responses to stated preference surveys
Journal of Environmental Economics and Management, 2018Co-Authors: James K Hammitt, Daniel HerreraaraujoAbstract:Abstract We develop validity tests for application to stated-preference estimates of WTP to reduce mortality risk, i.e., value per statistical life (VSL), and apply these to data obtained by surveying a representative sample of French adults over the internet. These tests (WTP nearly proportional to risk reduction, insensitive to small differences in baseline risk, increasing in income, and consistent with budget constraints) are satisfied by a conventional single-regression Analysis of our data. Using Latent Class Analysis (LCA), we identify important differences between respondents in their consistency with the validity tests and control for much of this heterogeneity. Estimates of VSL from the Latent Class that is consistent with the validity tests are smaller than estimates from the standard Analysis. We estimate mean VSL for adults of about 2 million € and for children (based on parents' WTP) of about 6 million €.
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peeling back the onion using Latent Class Analysis to uncover heterogeneous responses to stated preference surveys
Post-Print, 2017Co-Authors: James K Hammitt, Daniel HerreraaraujoAbstract:We develop validity tests for application to stated-preference estimates of WTP to reduce mortality risk, i.e., value per statistical life (VSL), and apply these to data obtained by surveying a representative sample of French adults over the internet. These tests (WTP nearly proportional to risk reduction, insensitive to small differences in baseline risk, increasing in income, and consistent with budget constraints) are satisfied by a conventional single-regression Analysis of our data. Using Latent Class Analysis (LCA), we identify important differences between respondents in their consistency with the validity tests and control for much of this heterogeneity. Estimates of VSL from the Latent Class that is consistent with the validity tests are smaller than estimates from the standard Analysis. We estimate mean VSL for adults of about 2 million e and for children (based on parents’ WTP) of about 6 million euros.
Wenchun Tai - One of the best experts on this subject based on the ideXlab platform.
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Latent Class Analysis of students mathematics learning strategies and the relationship between learning strategy and mathematical literacy
Universal Journal of Educational Research, 2015Co-Authors: Suwei Lin, Wenchun TaiAbstract:This study investigated how various mathematics learning strategies affect the mathematical literacy of students. The data for this study were obtained from the 2012 Programme for International Student Assessment (PISA) data of Taiwan. The PISA learning strategy survey contains three types of learning strategies: elaboration, control, and memorization. To objectively Classify students' learning strategies, we conducted a Latent Class Analysis (LCA) to determine the optimal fitting Latent Class model of students' performances on a learning strategy assessment and to explore the mathematical literacy of students who used various learning strategies. The result of the LCA showed that, among the models of two to five Classes, the model of four Classes was the optimally fitted model. The results of this study provide crucial information for mathematics educators regarding the achievement-related and strategy-related outcomes of schooling. By combining information from the assessment of mathematical literacy and survey of learning strategies that predispose students to using their mathematical literacy, a more complete picture of mathematics teaching and learning emerges. The implications of these results are discussed.
Pamela K Keel - One of the best experts on this subject based on the ideXlab platform.
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application of a Latent Class Analysis to empirically define eating disorder phenotypes
Archives of General Psychiatry, 2004Co-Authors: Cynthia M. Bulik, Katherine A Halmi, Pamela K Keel, Manfred M Fichter, Norbert Quadflieg, Mark G Baxter, Laura Thornton, Allan S Kaplan, Michael StroberAbstract:Context Diagnostic criteria for eating disorders influence how we recognize, research, and treat eating disorders, and empirically valid phenotypes are required for revealing their genetic bases. Objective To empirically define eating disorder phenotypes. Design Data regarding eating disorder symptoms and features from 1179 individuals with clinically significant eating disorders were submitted to a Latent Class Analysis. The resulting Latent Classes were compared on non–eating disorder variables in a series of validation analyses. Setting Multinational, collaborative study with cases ascertained through diverse clinical settings (inpatient, outpatient, and community). Participants Members of affected relative pairs recruited for participation in genetic studies of eating disorders in which probands met DSM-IV-TR criteria for anorexia nervosa (AN) or bulimia nervosa and had at least 1 biological relative with a clinically significant eating disorder. Main Outcome Measure Number and clinical characterization of Latent Classes. Results A 4-Class solution provided the best fit. Latent Class 1 (LC1) resembled restricting AN; LC2, AN and bulimia nervosa with the use of multiple methods of purging; LC3, restricting AN without obsessive-compulsive features; and LC4, bulimia nervosa with self-induced vomiting as the sole form of purging. Biological relatives were significantly likely to belong to the same Latent Class. Across validation analyses, LC2 demonstrated the highest levels of psychological disturbance, and LC3 demonstrated the lowest. Conclusions The presence of obsessive-compulsive features differentiates among individuals with restricting AN. Similarly, the combination of low weight and multiple methods of purging distinguishes among individuals with binge eating and purging behaviors. These results support some of the distinctions drawn within the DSM-IV - TR among eating disorder subtypes, while introducing new features to define phenotypes.
