NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 5 results Save | Export
Peer reviewed Peer reviewed
Beasley, T. Mark – Multivariate Behavioral Research, 2002
Through simulation, showed that a multivariate test of interactions for aligned ranks in a split-plot design controlled Type I error rates for nonnormal data with nonspherical covariance structures. This method also performed well in the presence of a strong repeated measures main effect and demonstrated more statistical power than parametric…
Descriptors: Interaction, Multivariate Analysis, Nonparametric Statistics, Simulation
Peer reviewed Peer reviewed
Katz, Barry M.; McSweeney, Maryellen – Multivariate Behavioral Research, 1980
An explicit statement of a statistic which is a nonparametric analog to one-way MANOVA is presented. The statistic is a multivariate extension of the nonparametric Kruskal-Wallis test (1952). In addition two post hoc procedures are developed and compared. (Author/JKS)
Descriptors: Analysis of Variance, Data Analysis, Multivariate Analysis, Nonparametric Statistics
Peer reviewed Peer reviewed
Chernyshenko, Oleksandr S.; Stark, Stephen; Chan, Kim-Yin; Drasgow, Fritz; Williams, Bruce – Multivariate Behavioral Research, 2001
Compared the fit of several Item Response Theory (IRT) models to two personality assessment instruments using data from 13,059 individuals responding to one instrument and 1,770 individuals responding to the other. Two- and three-parameter logistic models fit some scales reasonably well, but not others, and the graded response model generally did…
Descriptors: Adults, Comparative Analysis, Goodness of Fit, Item Response Theory
Peer reviewed Peer reviewed
Zwick, Rebecca – Multivariate Behavioral Research, 1986
The purpose of the current study was to investigate the relative performance of the parametric, rank, and normal scores procedures when the classical assumptions were met and under violations of these assumptions. This investigation included the normal scores as well as the rank test. (LMO)
Descriptors: Hypothesis Testing, Mathematical Models, Measurement Techniques, Monte Carlo Methods
Peer reviewed Peer reviewed
Olsson, Ulf – Multivariate Behavioral Research, 1979
The paper discusses the consequences for maximum likelihood factor analysis which may follow if the observed variables are ordinal with only a few scale steps. Results indicate that classification may lead to a substantial lack of fit of the model--an erroneous indication that more factors are needed. (Author/CTM)
Descriptors: Classification, Factor Analysis, Goodness of Fit, Maximum Likelihood Statistics