In this article, we pursue two points of discussion. First, a new illustration is presented of the person-oriented tenet according to which it can be hazardous to generalize to the individual results that are based on the analysis of aggregated data. Second, it is illustrated that taking into account serial dependence information can result in not…

This article presents a novel approach to introducing principal component analysis (PCA), using summary tables and descriptive statistics. Given its applicability across a variety of academic disciplines, this topic offers abundant opportunity for class discussion and activities. However, teaching PCA in an introductory class can be challenging…

Although many textbooks on multivariate statistics discuss the common factor analysis model, few of these books mention the problem of factor score indeterminacy (FSI). Thus, many students and contemporary researchers are unaware of an important fact. Namely, for any common factor model with known (or estimated) model parameters, infinite sets of…

Transfer beliefs are understudied in the training transfer field, whereas structural equation modelling (SEM) has been a widely used technique to study transfer models. New methodologies are needed to study training transfer and network analysis (NA) has emerged as a new approach that provides a visual representation of a given network. We…

A sample suffers range restriction (RR) when its variance is reduced comparing with its population variance and, in turn, it fails representing such population. If the RR occurs over the latent factor, not directly over the observed variable, the researcher deals with an indirect RR, common when using convenience samples. This work explores how…

Multiple-response questions are a common feature of survey-based research, as its advantages of information collection are well known. Statistical analysis of the responses, however, tends to be either one or two-dimensional, with the restrictions that this entails. This paper presents a multidimensional analysis protocol that provides the…

The use of personality inventories has been limited because of their cost and the length. To overcome these limitations, this study created the Personality Identity Estimator (PIE), an easy-to-use inventory to estimate personality types that can be used at no cost. PIE is a categorical inventory containing 12 items with 3 items for each of the 4…

Despite several theoretical, structural, and statistical issues reported against Five Facets Mindfulness Questionnaire (FFMQ), most studies in the educational sector of Pakistan use it without analyzing its factor structure. Since culture might change the structure, this first systematic study filled the gap and explored the factor structure of…

JMP® Pro has introduced a new structural equation modeling (SEM) platform to its suite of multivariate methods of analysis. Utilizing their graphical user interface, JMP Pro has created a SEM platform that is easily navigable for both experienced and novice SEM users. As a new platform, JMP Pro does not have the capacity to implement certain…

We describe a data mining pipeline to convert data from educational systems into knowledge component (KC) models. In contrast to other approaches, our approach employs and compares multiple model search methodologies (e.g., sparse factor analysis, covariance clustering) within a single pipeline. In this preliminary work, we describe our approach's…

Deciding which random effects to retain is a central decision in mixed effect models. Recent recommendations advise a maximal structure whereby all theoretically relevant random effects are retained. Nonetheless, including many random effects often leads to nonpositive definiteness. A typical remedy is to simplify the random effect structure by…

The study aimed to verify the psychometric properties of the emotional-style scale and explore different clusters of emotional styles. An emotional style scale was completed in three districts of western Taiwan using stratified random sampling. The study confirmed the reliability and convergent validity of each subscale in a sample of 712…

We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…

The relations among alternative parameterizations of the binary factor analysis (FA) model and two-parameter logistic (2PL) item response theory (IRT) model have been thoroughly discussed in literature (e.g., Lord & Novick, 1968; Takane & de Leeuw, 1987; McDonald, 1999; Wirth & Edwards, 2007; Kamata & Bauer, 2008). However, the…

Factor analysis is a statistical technique that is widely used in psychology and social sciences. Using computers and statistical packages, implementation of multivariate factor analysis and other multivariate methods becomes possible for researchers. Exploratory factor analysis and confirmatory factor analysis are applied in different studies;…