Predicting physical activity intention and behaviour using achievement goal theory: A person-centred analysis

The purpose of the current study was to identify the 2 × 2 achievement goals profiles at the intraindividual level using a latent profile analyses (LPA) approach while controlling for the nesting of students within classroom. Additional analyses involving the direct inclusion of predictors and outcomes to the final latent profile solution were also used to examine the relationships between the latent profiles and perceived motivational climate, intention to be physically active and physical activity participation. A sample of 1810 school children aged 14–19 years drawn from 79 classes in 13 Singaporean schools took part in the study. Using the latent profile analysis, four distinct motivational profiles could be identified. The results from multinomial logistic regressions showed that profile membership was significantly predicted by perceptions of mastery and performance climate. Finally, the results showed that the four profiles differed significantly in terms of intention to be physically active and physical activity participation.     

Profiles of Children’s Thinking About Violence in Families Exposed to Intimate Partner Violence

Intimate partner violence remains a pervasive and common social problem. Evidence indicates that children witness many instances of intimate partner violence. However, the structure of children’s thinking about family violence is still not well understood. This research employed latent profile analysis to identify underlying latent profiles of children’s thinking about violence using the Attitudes and Beliefs About Violence Scale. The analysis identified two latent profiles mostly differentiated by children’s beliefs about whether or not victims of violence deserve to have violence inflicted upon them. Several covariates differentiated members of the two profiles. Suggestions for intervention and practice are included.     

Extending latent class solutions to other variables

A procedure is derived for estimating the latent parameters of items not initially included in a latent class solution, on the assumption that the relations between those additional items and the original ones are accounted for by the same latent structure. A chi-square test is proposed for evaluating the relatedness of the additional items to the latent structure. The extension is generalized to associate continuous outside variables with the original solution, and this is accompanied by the suggestion that a simple analysis of variance be used to assess the results. Finally, this latent structure extension is compared with the Dwyer extension of factor analysis.I am grateful to J. J. Mellinger for clarifying discussions of the statistical portions of this paper.Opinions expressed herein are the author's, not the Army's.     

Estimating Cognitive Profiles Using Profile Analysis via Multidimensional Scaling (PAMS)

Two of the most popular methods of profile analysis, cluster analysis and modal profile analysis, have limitations. First, neither technique is adequate when the sample size is large. Second, neither method will necessarily provide profile information in terms of both level and pattern. A new method of profile analysis, called Profile Analysis via Multidimensional Scaling (PAMS; Davison, 1996), is introduced to meet the challenge. PAMS extends the use of simple multidimensional scaling methods to identify latent profiles in a multi-test battery. Application of PAMS to profile analysis is described. The PAMS model is then used to identify latent profiles from a subgroup (N = 357) within the sample of the Woodcock-Johnson Psychoeducational Battery-Revised (WJ-R; McGrew, Werder, & Woodcock, 1991; Woodcock & Johnson, 1989), followed by a discussion of procedures for interpreting participants' observed score profiles from the latent PAMS profiles. Finally, advantages and limitations of the PAMS technique are discussed.     

Three multivariate models: Factor analysis,latent structure analysis,and latent profile analysis

The factor analysis model and Lazarsfeld's latent structure scheme for analyzing dichotomous attributes are derived to show how the latter model avoids three knotty problems in factor analysis: communality estimation, rotation, and curvilinearity. Then the latent structure model is generalized into latent profile analysis for the study of interrelations among quantitative measures. Four latent profile examples are presented and discussed in terms of their limitations and the problems of latent metric and dimensionality thereby raised. The possibility of treating higher order empirical relations in a manner paralleling their various uses in the latent structure model is indicated.The latter model is anticipated in an earlier paper by Green [12].The major portion of this paper was completed at the Center for Advanced Study in the Behavioral Sciences. The opinions expressed are those of the author and are not to be construed as reflecting official Department of the Army policy.     

CFA Models with a General Factor and Multiple Sets of Secondary Factors

We propose a class of confirmatory factor analysis models that include multiple sets of secondary or specific factors and a general factor. The general factor accounts for the common variance among manifest variables, whereas multiple sets of secondary factors account for the remaining source-specific dependency among subsets of manifest variables. A special case of the model is further proposed which constrains the specific factor loadings to be proportional to the general factor loadings. This proportional model substantially reduces the number of model parameters while preserving the essential structure of the general model. Furthermore, the proportional model allows for the interpretation of latent variables as the expected values of the observed manifest variables, decomposition of the variances, and the inclusion of interactions, similar to generalizability theory. We provide two applications to illustrate the utility of the proposed class of models.     

Estimating latent correlations between repeated testings

A model for longitudinal latent structure analysis is proposed. We assume that test scores for a given mental or attitudinal test are observed for the same individuals at two different points in time. The purpose of the analysis is to fit a model that combines the values of the latent variable at the two time points in a two-dimensional latent density. The correlation coefficient between the two values of the latent variable can then be estimated. The theory and methods are illustrated by a Danish dataset concerning psychic vulnerability.     

Applying the Mixed Rasch Model to the Runco Ideational Behavior Scale

Previous research using creativity assessments has used latent class models and identified multiple classes (a 3-class solution) associated with various domains. This study explored the latent class structure of the Runco Ideational Behavior Scale, which was designed to quantify ideational capacity. A robust state-of the-art technique called the Mixed Rasch Model (MRM) was utilized with a sample of 765 Turkish middle school students. Consistent with previous studies, 3 clear latent classes were found in this study. Class 1 represents the regular ideators class, Class 2 the idea-producers class, and Class 3 the idea-averters class. In this study the 3-class solution represents 3 different skills, rather than 3 different domains. This study showed a promising application of MRMs as an alternative to the latent class analysis (LCA) technique for researchers in the field. The study also provided further evidence for the multiple class structure found in previous creativity assessments.     

An extension of Anderson's solution for the latent structure equations

Anderson's solution for the latent structure equations is summarized and then extended in two ways so as to involve all items simultaneously.This article was written while the author was employed at The University of North Carolina.     

Methodological and practical issues regarding phenomenological subtypes of highly suggestible individuals: A response to Kumar

A hypnotic induction produces different patterns of spontaneous experiences across individuals. The magnitude and characteristics of these responses covary moderately with hypnotic suggestibility, but also differ within levels of hypnotic suggestibility. This study sought to identify discrete phenomenological profiles in response to a hypnotic induction and assess whether experiential variability among highly suggestible individuals matches the phenomenological profiles predicted by dissociative typological models of high hypnotic suggestibility. Phenomenological state scores indexed in reference to a resting epoch during hypnosis were submitted to a latent profile analysis. The profiles in the derived four-class solution differed in multiple experiential dimensions and hypnotic suggestibility. Highly suggestible individuals were distributed across two classes that exhibited response patterns suggesting an inward attention subtype and a dissociative subtype. These results provide support for dissociative typological models of high hypnotic suggestibility and indicate that highly suggestible individuals do not display a uniform response to a hypnotic induction.     

Differential patterns of spontaneous experiential response to a hypnotic induction: A latent profile analysis

A hypnotic induction produces different patterns of spontaneous experiences across individuals. The magnitude and characteristics of these responses covary moderately with hypnotic suggestibility, but also differ within levels of hypnotic suggestibility. This study sought to identify discrete phenomenological profiles in response to a hypnotic induction and assess whether experiential variability among highly suggestible individuals matches the phenomenological profiles predicted by dissociative typological models of high hypnotic suggestibility. Phenomenological state scores indexed in reference to a resting epoch during hypnosis were submitted to a latent profile analysis. The profiles in the derived four-class solution differed in multiple experiential dimensions and hypnotic suggestibility. Highly suggestible individuals were distributed across two classes that exhibited response patterns suggesting an inward attention subtype and a dissociative subtype. These results provide support for dissociative typological models of high hypnotic suggestibility and indicate that highly suggestible individuals do not display a uniform response to a hypnotic induction.     

Using Profile Analysis via Multidimensional Scaling (PAMS) to identify core profiles from the WMS-III

Profile Analysis via Multidimensional Scaling (PAMS) is a procedure for extracting latent core profiles in a multitest data set. The PAMS procedure offers several advantages compared with other profile analysis procedures. Most notably, PAMS estimates individual profile weights that reflect the degree to which an individual's observed profile approximates the shape and scatter of latent core profiles. The PAMS procedure was applied to index scores of nonreplicated participants from the standardization sample (N = 1,033) for the Wechsler Memory Scale--Third Edition (D. Tulsky, J. Zhu, & M. F. Ledbetter, 2002). PAMS extracted discrepant visual memory and auditory memory versus working memory core profiles for the complete 16- to 89-year-old sample and discrepant working memory and auditory memory versus working memory core profiles for the 75- to 89-year-old cohort. Implications for use of PAMS in future research are discussed.     

Taxometric and factor analytic models of anxiety sensitivity: integrating approaches to latent structural research

This study represents an effort to better understand the latent structure of anxiety sensitivity (AS), as indexed by the 16-item Anxiety Sensitivity Index (ASI; S. Reiss, R. A. Peterson, M. Gursky, & R. J. McNally, 1986), by using taxometric and factor-analytic approaches in an integrative manner. Taxometric analyses indicated that AS has a taxonic latent class structure (i.e., a dichotomous latent class structure) in a large sample of North American adults (N=2,515). As predicted, confirmatory factor analyses indicated that a multidimensional 3-factor model of AS provided a good fit for the AS complement class (normative or low-risk form) but not the AS taxon class (high-risk form). Exploratory factor analytic results suggested that the AS taxon may demonstrate a unique, unidimensional factor solution, though there are alternative indications that it may be characterized by a 2-factor solution. Findings suggest that the latent structural nature of AS can be conceptualized as a taxonic latent class structure composed of 2 types or forms of AS, each of these forms characterized by its own unique latent continuity and dimensional structure.     

A latent variable approach to executive control in healthy ageing

It is a well-established finding that the central executive is fractionated in at least three separable component processes: Updating, Shifting, and Inhibition of information (Miyake et al., 2000). However, the fractionation of the central executive among the elderly has been less well explored, and Miyake's et al. latent structure has not yet been integrated with other models that propose additional components, such as access to long-term information. Here we administered a battery of classic and newer neuropsychological tests of executive functions to 122 healthy individuals aged between 48 and 91 years. The test scores were subjected to a latent variable analysis (LISREL), and yielded four factors. The factor structure obtained was broadly consistent with Miyake et al.'s three-factor model. However, an additional factor, which was labeled 'efficiency of access to long-term memory', and a mediator factor ('speed of processing') were apparent in our structural equation analysis. Furthermore, the best model that described executive functioning in our sample of healthy elderly adults included a two-factor solution, thus indicating a possible mechanism of dedifferentiation, which involves larger correlations and interdependence of latent variables as a consequence of cognitive ageing. These results are discussed in the light of current models of prefrontal cortex functioning.     

An empirical comparison of restricted and general latent distance analysis

Latent distance analysis provides a probability model for the non-perfect Guttman scale; the restricted latent distance structure is simpler to compute than the general structure. Since no sampling theory for latent structure analysis is available, the advantages of the general structure cannot be expressed formally. The two structures are compared in terms of their fit to fifteen sets of empirical data. The computation schemes used are summarized.     

A Unified Framework for the Comparison of Treatments with Ordinal Responses

Different latent variable models have been used to analyze ordinal categorical data which can be conceptualized as manifestations of an unobserved continuous variable. In this paper, we propose a unified framework based on a general latent variable model for the comparison of treatments with ordinal responses. The latent variable model is built upon the location-scale family and is rich enough to include many important existing models for analyzing ordinal categorical variables, including the proportional odds model, the ordered probit-type model, and the proportional hazards model. A flexible estimation procedure is proposed for the identification and estimation of the general latent variable model, which allows for the location and scale parameters to be freely estimated. The framework advances the existing methods by enabling many other popular models for analyzing continuous variables to be used to analyze ordinal categorical data, thus allowing for important statistical inferences such as location and/or dispersion comparisons among treatments to be conveniently drawn. Analysis on real data sets is used to illustrate the proposed methods.     

Patterns of hypnotic response,revisited

It has long been speculated that there are discrete patterns of responsiveness to hypnotic suggestions, perhaps paralleling the factor structure of hypnotizability. An earlier study by Brenneman and Kihlstrom (1986), employing cluster analysis, found evidence for 12 such profiles. A new study by Terhune (2015), employing latent profile analysis, found evidence for three such patterns among highly hypnotizable subjects, and a fourth comprising subjects of medium hypnotizability. Some differences between the two studies are described. Convincing identification of discrete “types” of high hypnotizability, such as dissociative and nondissociative, may require a larger dataset than is currently available, but also data pertaining directly to divisions in conscious awareness and experienced involuntariness.     

A latent variable model for discrete multivariate psychometric waiting times

A version of the discrete proportional hazards model is developed for psychometrical applications. In such applications, a primary covariate that influences failure times is a latent variable representing a psychological construct. The Metropolis-Hastings algorithm is studied as a method for performing marginal likelihood inference on the item parameters. The model is illustrated with a real data example that relates the age at which teenagers first experience various substances to the latent ability to avoid the onset of such behaviors.We thank Michael Newton and Daode Huang for their helpful comments and suggestions.     

A latent variable modeling approach to identifying subtypes of serious and violent female juvenile offenders

Females have recently become an important population in research related to serious and violent juvenile offending. Although a small body of research exists on girls in the deep end of the system, very few studies have examined the degree of heterogeneity within high-risk female samples. This study applied latent class analysis (LCA) to identify subgroups of female juvenile offenders based on their self-report of offending profiles (N=133). Results supported a three-class solution with subgroups characterized by patterns of 'violent and delinquent', 'delinquency only', and 'low' offending patterns. The LCA solution was replicated in an independent sample of high-risk females. The 'violent and delinquent' class was characterized by significantly higher rates of DSM-IV diagnoses for internalizing disorders, affect dysregulation, exposure to violence (within the home, school and neighborhood), and familial histories of criminality. Implications for future research, policy and clinical practice are discussed.