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Sample Size Calculation for Estimating or Testing a Nonzero Squared Multiple Correlation Coefficient
Krishnamoorthy, K.; Xia, Yanping – Multivariate Behavioral Research, 2008
The problems of hypothesis testing and interval estimation of the squared multiple correlation coefficient of a multivariate normal distribution are considered. It is shown that available one-sided tests are uniformly most powerful, and the one-sided confidence intervals are uniformly most accurate. An exact method of calculating sample size to…
Descriptors: Statistical Analysis, Intervals, Sample Size, Testing

Kaplan, David – Multivariate Behavioral Research, 1999
Proposes an extension of the propensity score adjustment method to the analysis of group differences on latent variable models. Uses multiple indicators-multiple causes (MIMIC) structural equation modeling to test hypotheses about treatment group differences. Discusses the role of factorial invariance as it relates to this approach. (SLD)
Descriptors: Groups, Hypothesis Testing, Scores, Structural Equation Models

Levin, Joseph – Multivariate Behavioral Research, 1986
The relation between the power of a significance test in a block design with correlated measurements and the reliability of the measuring instrument is analyzed in terms of the components of variance entering the reliability coefficient and the noncentrality parameter. (Author/LMO)
Descriptors: Analysis of Variance, Hypothesis Testing, Mathematical Models, Power (Statistics)

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