A general multivariate latent growth model with applications in student careers Data warehouses

The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context the analysis of student performance and capabilities plays a fundamental role. In this work we propose a multivariate latent growth model for studying the performances of a cohort of students of the University of Bologna. The model proposed is innovative since it is composed by: (1) multivariate growth models that allow to capture the different dynamics of student performance indicators over time and (2) a factor model that allows to measure the general latent student capability. The flexibility of the model proposed allows its applications in several fields such as socio-economic settings in which personal behaviours are studied by using panel data.Comment: 20 page

Confirmatory factor analysis of the Valencia scale on attitudes and beliefs toward hypnosis, therapist version

Health professionals' beliefs and attitudes toward hypnosis may make them reluctant to use it or even to foster misapplications and iatrogenic uses of hypnosis. The Valencia Scale on Attitudes and Beliefs toward Hypnosis-Therapist version (VSABH-T) is a specific instrument to evaluate therapists' attitudes and beliefs. The aims of this study are to evaluate the 8-factor structure of the VSABH-T proposed from a confirmatory perspective. The sample comprised 1,661 licensed psychologists who are members of the Spanish Psychological Association for the initial test and 787 for the retest. Results confirmed the 8-factor structure obtained in a previous exploratory study, namely: Fear, Memory, Help, Control, Collaboration, Interest, Magic, and Marginal. The scale also showed adequate psychometric properties, including good internal consistency and test-retest reliability

Using LISREL to analyze genetic and environmental covariance structure

Describes a method in which the linear structural relationships (LISREL) computer program is used for the genetic analysis of covariance structure. The method is illustrated with simulated and published twin data, including an analysis of twin data by N. G. Martin et al (1981) on psychomotor performance during alcohol intoxication

A framework for power analysis using a structural equation modelling procedure

BACKGROUND: This paper demonstrates how structural equation modelling (SEM) can be used as a tool to aid in carrying out power analyses. For many complex multivariate designs that are increasingly being employed, power analyses can be difficult to carry out, because the software available lacks sufficient flexibility. Satorra and Saris developed a method for estimating the power of the likelihood ratio test for structural equation models. Whilst the Satorra and Saris approach is familiar to researchers who use the structural equation modelling approach, it is less well known amongst other researchers. The SEM approach can be equivalent to other multivariate statistical tests, and therefore the Satorra and Saris approach to power analysis can be used. METHODS: The covariance matrix, along with a vector of means, relating to the alternative hypothesis is generated. This represents the hypothesised population effects. A model (representing the null hypothesis) is then tested in a structural equation model, using the population parameters as input. An analysis based on the chi-square of this model can provide estimates of the sample size required for different levels of power to reject the null hypothesis. CONCLUSIONS: The SEM based power analysis approach may prove useful for researchers designing research in the health and medical spheres

A theory-based approach to understanding condom errors and problems reported by men attending an STI clinic

The official published version can be accessed from the link below - Copyright @ 2008 Springer VerlagWe employed the information–motivation–behavioral skills (IMB) model to guide an investigation of correlates for correct condom use among 278 adult (18–35 years old) male clients attending a sexually transmitted infection (STI) clinic. An anonymous questionnaire aided by a CD-recording of the questions was administered. Linear Structural Relations Program was used to conduct path analyses of the hypothesized IMB model. Parameter estimates showed that while information did not directly affect behavioral skills, it did have a direct (negative) effect on condom use errors. Motivation had a significant direct (positive) effect on behavioral skills and a significant indirect (positive) effect on condom use errors through behavioral skills. Behavioral skills had a direct (negative) effect on condom use errors. Among men attending a public STI clinic, these findings suggest brief, clinic-based, safer sex programs for men who have sex with women should incorporate activities to convey correct condom use information, instill motivation to use condoms correctly, and directly enhance men’s behavioral skills for correct use of condoms

On Passion and Sports Fans:A Look at Football

The purpose of the present research was to test the applicability of the Dualistic Model of Passion (Vallerand et al., 2003) to being a sport (football) fan. The model posits that passion is a strong inclination toward an activity that individuals like (or even love), that they value, and in which they invest time and energy. Furthermore, two types of passion are proposed: harmonious and obsessive passion. While obsessive passion entails an uncontrollable urge to engage in the passionate activity, harmonious passion entails a sense of volition while engaging in the activity. Finally, the model posits that harmonious passion leads to more adaptive outcomes than obsessive passion. Three studies provided support for this dualistic conceptualization of passion. Study 1 showed that harmonious passion was positively associated with adaptive behaviours (e.g., celebrate the team’s victory), while obsessive passion was rather positively associated with maladaptive behaviours (e.g., to risk losing one’s employment to go to the team’s game). Study 2 used a short Passion Scale and showed that harmonious passion was positively related to the positive affective life of fans during the 2006 FIFA World Cup, psychological health (self-esteem and life satisfaction), and public displays of adaptive behaviours (e.g., celebrating one’s team victory in the streets), while obsessive passion was predictive of maladaptive affective life (e.g., hating opposing team’s fans) and behaviours (e.g., mocking the opposing team’s fans). Finally, Study 3 examined the role of obsessive passion as a predictor of partner’s conflict that in turn undermined partner’s relationship satisfaction. Overall, the present results provided support for the Dualistic Model of Passion. The conceptual and applied implications of the findings are discussed

Simultaneous genetic analysis of longitudinal means and covariance structure in the simplex model using twin data

A longitudinal model based on the simplex model is presented to analyze simultaneously means and covariance structure using univariate longitudinal twin data. The objective of the model is to decompose the mean trend into components which can be attributed to those genetic and environmental factors which give rise to phenotypic individual differences and a component of unknown constitution which does not involve individual differences. Illustrations are given using simulated data and repeatedly measured weight obtained in a sample of 82 female twin pairs on sbc occasions. KEY WORDS: repeated measures; genetic and environmental covariance structure; mean trend; longitudinal twin data; genetic simplex mode; LISREL

Sparse Exploratory Factor Analysis

Sparse principal component analysis is a very active research area in the last decade. It produces component loadings with many zero entries which facilitates their interpretation and helps avoid redundant variables. The classic factor analysis is another popular dimension reduction technique which shares similar interpretation problems and could greatly benefit from sparse solutions. Unfortunately, there are very few works considering sparse versions of the classic factor analysis. Our goal is to contribute further in this direction. We revisit the most popular procedures for exploratory factor analysis, maximum likelihood and least squares. Sparse factor loadings are obtained for them by, first, adopting a special reparameterization and, second, by introducing additional [Formula: see text]-norm penalties into the standard factor analysis problems. As a result, we propose sparse versions of the major factor analysis procedures. We illustrate the developed algorithms on well-known psychometric problems. Our sparse solutions are critically compared to ones obtained by other existing methods

Factor copula models for item response data

Factor or conditional independence models based on copulas are proposed for multivariate discrete data such as item responses. The factor copula models have interpretations of latent maxima/minima (in comparison with latent means) and can lead to more probability in the joint upper or lower tail compared with factor models based on the discretized multivariate normal distribution (or multidimensional normal ogive model). Details on maximum likelihood estimation of parameters for the factor copula model are given, as well as analysis of the behavior of the log-likelihood. Our general methodology is illustrated with several item response data sets, and it is shown that there is a substantial improvement on existing models both conceptually and in fit to data