Abstract Researchers in the social and behavioral sciences are frequently concerned whether the c... more Abstract Researchers in the social and behavioral sciences are frequently concerned whether the constructs they study should be represented as categorical types (classes) or continuous traits (factors). Two approaches to testing such type versus trait hypotheses are Meehlian taxometric procedures and the factor mixture model (FMM). The use of taxometric procedures and the more recently developed FMM has dramatically increased in the last ten years, and initial comparisons have shown that the latent structures that can be detected ...
Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a... more Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a structural equation model within each class. Fitting SEMMs is illustrated using data from one wave of the Notre Dame Longitudinal Study of Aging. Based on the model used in the illustration, SEMM parameter estimation and correct class assignment are investigated in a large scale simulation study. Design factors of the simulation study are (im)balanced class proportions, (im)balanced factor variances, sample size, and class separation. We compare the fit of models with correct and misspecified within-class structural relations. In addition, we investigate the potential to fit SEMMs with binary indicators. The structure of within-class distributions can be recovered under a wide variety of conditions, indicating the general potential and flexibility of SEMMs to test complex within-class models. Correct class assignment is limited.
Few studies have compared persons in treatment to those not in treatment with regard to perceived... more Few studies have compared persons in treatment to those not in treatment with regard to perceived stigma. We surveyed soldiers to examine differences in stigma perceptions among those in treatment for substance abuse and/or mental health problems (n= 470) and those not in treatment (n= 966). Analyses revealed that soldiers in treatment perceived greater stigma regarding mental health treatment compared with soldiers not in treatment. These findings support the notion that personnel most in need of treatment perceive ...
Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths an... more Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths and weaknesses. Both approaches purport to detect evidence of a latent class structure. Taxometric procedures, popular in psychiatric and psychopathology literature, make no assumptions beyond those needed to compute means and covariances. However, Taxometric procedures assume that observed items are uncorrelated within a class or taxon. This assumption is violated when there are individual differences in the trait underlying the ...
UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collectio... more UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collection of dissertations and theses. Learn more... ProQuest, Maternal worry about infant health, maternal anxiety, and maternal perceptions of child ...
Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class c... more Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class clustering, but they have very different sets of strengths and weaknesses. Taxometric procedures, popular in psychiatric and psychopathology applications, do not rely on distributional assumptions. Their sole purpose is to detect the presence of latent classes. The procedures capitalize on the assumption that, due to mean differences between two classes, item covariances within class are smaller than item covariances between the classes. FMM goes beyond class detection and permits the specification of hypothesis-based within-class covariance structures ranging from local independence to multidimensional within-class factor models. In principle, FMM permits the comparison of alternative models using likelihood-based indexes. These advantages come at the price of distributional assumptions. In addition, models are often highly parameterized and susceptible to misspecifications of the within-class covariance structure. Following an illustration with an empirical data set of binary depression items, the MAXEIG procedure and FMM are compared in a simulation study focusing on class detection and the assignment of subjects to the latent classes. FMM generally outperformed MAXEIG in terms of class detection and class assignment. Substantially different class sizes negatively impacted the performance of both approaches, whereas low class separation was much more problematic for MAXEIG than for the FMM.
Abstract Researchers in the social and behavioral sciences are frequently concerned whether the c... more Abstract Researchers in the social and behavioral sciences are frequently concerned whether the constructs they study should be represented as categorical types (classes) or continuous traits (factors). Two approaches to testing such type versus trait hypotheses are Meehlian taxometric procedures and the factor mixture model (FMM). The use of taxometric procedures and the more recently developed FMM has dramatically increased in the last ten years, and initial comparisons have shown that the latent structures that can be detected ...
Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a... more Structural Equation Mixture Models(SEMMs) are latent class models that permit the estimation of a structural equation model within each class. Fitting SEMMs is illustrated using data from one wave of the Notre Dame Longitudinal Study of Aging. Based on the model used in the illustration, SEMM parameter estimation and correct class assignment are investigated in a large scale simulation study. Design factors of the simulation study are (im)balanced class proportions, (im)balanced factor variances, sample size, and class separation. We compare the fit of models with correct and misspecified within-class structural relations. In addition, we investigate the potential to fit SEMMs with binary indicators. The structure of within-class distributions can be recovered under a wide variety of conditions, indicating the general potential and flexibility of SEMMs to test complex within-class models. Correct class assignment is limited.
Few studies have compared persons in treatment to those not in treatment with regard to perceived... more Few studies have compared persons in treatment to those not in treatment with regard to perceived stigma. We surveyed soldiers to examine differences in stigma perceptions among those in treatment for substance abuse and/or mental health problems (n= 470) and those not in treatment (n= 966). Analyses revealed that soldiers in treatment perceived greater stigma regarding mental health treatment compared with soldiers not in treatment. These findings support the notion that personnel most in need of treatment perceive ...
Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths an... more Taxometric procedures and the Factor Mixture Model (FMM) have a complimentary set of strengths and weaknesses. Both approaches purport to detect evidence of a latent class structure. Taxometric procedures, popular in psychiatric and psychopathology literature, make no assumptions beyond those needed to compute means and covariances. However, Taxometric procedures assume that observed items are uncorrelated within a class or taxon. This assumption is violated when there are individual differences in the trait underlying the ...
UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collectio... more UMI, ProQuest ® Dissertations & Theses. The world's most comprehensive collection of dissertations and theses. Learn more... ProQuest, Maternal worry about infant health, maternal anxiety, and maternal perceptions of child ...
Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class c... more Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class clustering, but they have very different sets of strengths and weaknesses. Taxometric procedures, popular in psychiatric and psychopathology applications, do not rely on distributional assumptions. Their sole purpose is to detect the presence of latent classes. The procedures capitalize on the assumption that, due to mean differences between two classes, item covariances within class are smaller than item covariances between the classes. FMM goes beyond class detection and permits the specification of hypothesis-based within-class covariance structures ranging from local independence to multidimensional within-class factor models. In principle, FMM permits the comparison of alternative models using likelihood-based indexes. These advantages come at the price of distributional assumptions. In addition, models are often highly parameterized and susceptible to misspecifications of the within-class covariance structure. Following an illustration with an empirical data set of binary depression items, the MAXEIG procedure and FMM are compared in a simulation study focusing on class detection and the assignment of subjects to the latent classes. FMM generally outperformed MAXEIG in terms of class detection and class assignment. Substantially different class sizes negatively impacted the performance of both approaches, whereas low class separation was much more problematic for MAXEIG than for the FMM.
Uploads
Papers by Stephen Tueller