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Ho, Sammy K.; Chan, Edmund S. – Cogent Education, 2017
This study aims to investigate the psychometric properties of the revised multidimensional scale of perceived social support (R-MSPSS) for Chinese school teachers. A questionnaire comprising the R-MSPSS and other psychological measures was administered to a sample of 539 school teachers in Hong Kong. A series of confirmatory factor analysis was…
Descriptors: Multidimensional Scaling, Social Support Groups, Program Validation, Psychometrics
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Rhemtulla, Mijke; Brosseau-Liard, Patricia E.; Savalei, Victoria – Psychological Methods, 2012
A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…
Descriptors: Factor Analysis, Computation, Simulation, Sample Size
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Ferrando, Pere J. – Applied Psychological Measurement, 2009
Spearman's factor-analytic model has been proposed as a unidimensional linear item response theory (IRT) model for continuous item responses. This article first proposes a reexpression of the model that leads to a form similar to that of standard IRT models for binary responses and discusses the item indices of difficulty discrimination and…
Descriptors: Factor Analysis, Item Response Theory, Discriminant Analysis, Psychometrics
Takane, Yoshio – 1980
A maximum likelihood estimation procedure is developed for the simple and the weighted additive models. The data are assumed to be taken by either one of the following methods: (1) categorical ratings--the subject is asked to rate a set of stimuli with respect to an attribute of the stimuli on rating scales with a relatively few observation…
Descriptors: Data Collection, Elementary Education, Factor Analysis, Mathematical Models
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DeSarbo, Wayne S.; Cho, Jaewun – Psychometrika, 1989
This paper presents a new stochastic multidimensional scaling vector threshold model designed to analyze "pick any/n" choice data. A maximum likelihood procedure is formulated to estimate a joint space of both individuals and stimuli. The non-linear probit type model is described, and a Monte Carlo analysis is performed. (TJH)
Descriptors: Consumer Economics, Equations (Mathematics), Factor Analysis, Maximum Likelihood Statistics