NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 6 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Lee, Chun-Ting; Zhang, Guangjian; Edwards, Michael C. – Multivariate Behavioral Research, 2012
Exploratory factor analysis (EFA) is often conducted with ordinal data (e.g., items with 5-point responses) in the social and behavioral sciences. These ordinal variables are often treated as if they were continuous in practice. An alternative strategy is to assume that a normally distributed continuous variable underlies each ordinal variable.…
Descriptors: Personality Traits, Intervals, Monte Carlo Methods, Factor Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Steyn, H. S., Jr.; Ellis, S. M. – Multivariate Behavioral Research, 2009
When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…
Descriptors: Effect Size, Multivariate Analysis, Computation, Monte Carlo Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Steinley, Douglas; McDonald, Roderick P. – Multivariate Behavioral Research, 2007
Similarities between latent class models with K classes and linear factor models with K-1 factors are investigated. Specifically, the mathematical equivalence between the covariance structure of the two models is discussed, and a Monte Carlo simulation is performed using generated data that represents both latent factors and latent classes with…
Descriptors: Monte Carlo Methods, Item Response Theory, Factor Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Shieh, Gwowen – Multivariate Behavioral Research, 2009
In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…
Descriptors: Social Science Research, Sample Size, Monte Carlo Methods, Validity
Peer reviewed Peer reviewed
Direct linkDirect link
Hwang, Heungsun; Takane, Yoshio; DeSarbo, Wayne S. – Multivariate Behavioral Research, 2007
The growth curve model has been a useful tool for the analysis of repeated measures data. However, it is designed for an aggregate-sample analysis based on the assumption that the entire sample of respondents are from a single homogenous population. Thus, this method may not be suitable when heterogeneous subgroups exist in the population with…
Descriptors: Equations (Mathematics), Antisocial Behavior, Computation, Child Behavior
Peer reviewed Peer reviewed
Direct linkDirect link
Song, Xin-Yuan; Lee, Sik-Yum – Multivariate Behavioral Research, 2006
In this article, we formulate a nonlinear structural equation model (SEM) that can accommodate covariates in the measurement equation and nonlinear terms of covariates and exogenous latent variables in the structural equation. The covariates can come from continuous or discrete distributions. A Bayesian approach is developed to analyze the…
Descriptors: Structural Equation Models, Bayesian Statistics, Markov Processes, Monte Carlo Methods