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Ferrari, Pier Alda; Barbiero, Alessandro – Multivariate Behavioral Research, 2012
The increasing use of ordinal variables in different fields has led to the introduction of new statistical methods for their analysis. The performance of these methods needs to be investigated under a number of experimental conditions. Procedures to simulate from ordinal variables are then required. In this article, we deal with simulation from…
Descriptors: Data, Statistical Analysis, Sampling, Simulation
Varriale, Roberta; Vermunt, Jeroen K. – Multivariate Behavioral Research, 2012
Factor analysis is a statistical method for describing the associations among sets of observed variables in terms of a small number of underlying continuous latent variables. Various authors have proposed multilevel extensions of the factor model for the analysis of data sets with a hierarchical structure. These Multilevel Factor Models (MFMs)…
Descriptors: Factor Analysis, Models, Statistical Analysis, Maximum Likelihood Statistics
de Rooij, Mark; Schouteden, Martijn – Multivariate Behavioral Research, 2012
Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical…
Descriptors: Statistical Analysis, Longitudinal Studies, Data, Models
Wang, Lijuan; Grimm, Kevin J. – Multivariate Behavioral Research, 2012
Reliabilities of the two most widely used intraindividual variability indicators, "ISD[superscript 2]" and "ISD", are derived analytically. Both are functions of the sizes of the first and second moments of true intraindividual variability, the size of the measurement error variance, and the number of assessments within a burst. For comparison,…
Descriptors: Reliability, Statistical Analysis, Measurement, Models
Austin, Peter C. – Multivariate Behavioral Research, 2011
The propensity score is the probability of treatment assignment conditional on observed baseline characteristics. The propensity score allows one to design and analyze an observational (nonrandomized) study so that it mimics some of the particular characteristics of a randomized controlled trial. In particular, the propensity score is a balancing…
Descriptors: Probability, Scores, Statistical Analysis, Computation
Hayton, James C. – Multivariate Behavioral Research, 2009
In the article "Exploring the Sensitivity of Horn's Parallel Analysis to the Distributional Form of Random Data," Dinno (this issue) provides strong evidence that the distribution of random data does not have a significant influence on the outcome of the analysis. Hayton appreciates the thorough approach to evaluating this assumption, and agrees…
Descriptors: Research Methodology, Statistical Distributions, Evaluation, Statistical Analysis
Shiyko, Mariya P.; Ram, Nilam – Multivariate Behavioral Research, 2011
Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread,…
Descriptors: Generalizability Theory, Intervals, Smoking, Self Efficacy
Kenny, David A. – Multivariate Behavioral Research, 2010
DataToText is a project developed where the user communicates the relevant information for an analysis and DataToText computer routine produces text output that describes in words, tables, and figures the results from the analyses. Two extended examples are given, one an example of a moderator analysis and the other an example of a dyadic data…
Descriptors: Data Analysis, Computer Software, Statistical Analysis, Instruction
Halpin, Peter F.; Maraun, Michael D. – Multivariate Behavioral Research, 2010
A method for selecting between K-dimensional linear factor models and (K + 1)-class latent profile models is proposed. In particular, it is shown that the conditional covariances of observed variables are constant under factor models but nonlinear functions of the conditioning variable under latent profile models. The performance of a convenient…
Descriptors: Models, Selection, Vocational Evaluation, Developmental Psychology
Long, Jeffrey D.; Loeber, Rolf; Farrington, David P. – Multivariate Behavioral Research, 2009
Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…
Descriptors: Computation, Inferences, Crime, Models
A Class of Population Covariance Matrices in the Bootstrap Approach to Covariance Structure Analysis
Yuan, Ke-Hai; Hayashi, Kentaro; Yanagihara, Hirokazu – Multivariate Behavioral Research, 2007
Model evaluation in covariance structure analysis is critical before the results can be trusted. Due to finite sample sizes and unknown distributions of real data, existing conclusions regarding a particular statistic may not be applicable in practice. The bootstrap procedure automatically takes care of the unknown distribution and, for a given…
Descriptors: Multivariate Analysis, Statistical Analysis, Statistical Inference, Matrices
Peer reviewedCorter, James E. – Multivariate Behavioral Research, 1998
Describes a new combinatorial algorithm for fitting additive trees to proximity data. This generalized triples method examines all triples of objects of interest in relation to the remaining set of objects to be clustered. The procedure is illustrated, and a simulation study shows its advantages. (SLD)
Descriptors: Algorithms, Simulation, Statistical Analysis
Peer reviewedKroonenberg, Pieter M.; Lombardo, Rosaria – Multivariate Behavioral Research, 1999
Suggests using nonsymmetric correspondence analysis to evaluate contingency tables with a dependence structure. Presents a nontechnical overview with the relevant formulas in an appendix. Illustrates the technique with three examples from diverse areas. (SLD)
Descriptors: Evaluation Methods, Statistical Analysis
Bauer, Daniel J. – Multivariate Behavioral Research, 2007
Psychologists are applying growth mixture models at an increasing rate. This article argues that most of these applications are unlikely to reproduce the underlying taxonic structure of the population. At a more fundamental level, in many cases there is probably no taxonic structure to be found. Latent growth classes then categorically approximate…
Descriptors: Psychological Studies, Psychologists, Data Analysis, Psychology
Raykov, Tenko – Multivariate Behavioral Research, 2006
A method for examining invariance in validity of multiple-component instruments in repeated measure designs is outlined. The approach is developed within the framework of covariance structure modeling and is applicable for purposes of ascertaining temporal stability in scale validity. In addition, the procedure provides a range of plausible values…
Descriptors: Longitudinal Studies, Evaluation Methods, Test Validity, Item Analysis
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