This study aims to apply the model principal component analysis to reduce multicollinearity on variable currency exchange rate in eight countries in Asia against US Dollar including the Yen (Japan), Won (South Korea), Dollar (Hong Kong), Yuan (China), Bath (Thailand), Rupiah (Indonesia), Ringgit (Malaysia), Dollar (Singapore). It looks at yield…

We examine the performance of planned missing (PM) designs for correlated latent growth curve models. Using simulated data from a model where latent growth curves are fitted to two constructs over five time points, we apply three kinds of planned missingness. The first is item-level planned missingness using a three-form design at each wave such…

I discuss the recommendations and cautions in Steinley and Brusco's (2011) article on the use of finite models to cluster a data set. In their article, much use is made of comparison with the "K"-means procedure. As noted by researchers for over 30 years, the "K"-means procedure can be viewed as a special case of finite mixture modeling in which…

A general program for item-response analysis is described that uses the stabilized Newton-Raphson algorithm. This program is written to be compliant with Fortran 2003 standards and is sufficiently general to handle independent variables, multidimensional ability parameters, and matrix sampling. The ability variables may be either polytomous or…

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…

Problems of sampling error and accumulated rounding error in canonical variate analysis are discussed. A new technique is presented which appears to be superior to canonical variate analysis when the ratio of variables to sampling units is greater than one to ten. Examples are presented. (Author/JKS)

The triangular decomposition method is suggested as a general technique for obtaining the various measures of an ill-conditioned matrix. The advantages of using triangular decomposition are computing nicety, cost, and parsimony. (Author/PN)

Recent work (EJ 208 813) showing that generalized eigenvalue problems in which both matrices are singular can be solved by reducing them to similar problems of smaller order is discussed. Possible extensions of the work are indicated. (Author/JKS)

A general model is developed for the analysis of multivariate multilevel data structures. Special cases of this model include: repeated measures designs; multiple matrix samples; multilevel latent variable models; multiple time series and variance and covariance component models. (Author)

Extending the definitions of part and bipartial correlation to sets of variates, the notion of part and bipartial canonical correlation analysis are developed and illustrated. (Author)

The mathematical extension from scalars to matrices as a prerequisite for univariate to multivariate generalizations of statistical concepts and methods is discussed. One reason for several alternative techniques is the multitude of ways to generalize from univariate concepts to multivariate concepts. The additional complexity, and lack of…

This paper reviews and develops summary measures of associations between multiple sets of variables through the application of canonical correlation analysis. These measures are subsequently applied to a specific research problem: a study of the determinants of housing status. Some of the data analysis situations for which canonical correlation is…

Both doubly multivariate and multivariate mixed models of analyzing repeated measures on multivariate responses are reviewed. Given multivariate normality, a condition called multivariate sphericity of the covariance matrix is both necessary and sufficient for the validity of the multivariate mixed model analysis. (SLD)

Part and bi-partial canonical correlations were developed by extending the definitions of part and bi-partial correlation to sets of variates. These coefficients may be used to help researchers explore relationships which exist among several sets of normally distributed variates. (Author)

Standardization procedures in discriminant analysis are discussed. Three leading software packages--SPSSX, BMDP, and SAS--are compared in terms of their calculations of unstandardized and standardized discriminant coefficients. Estimation procedures are described for each. Arguments are presented for within-group, rather than total, variance…