We present a 3-step approach to defining latent growth components. In the first step, a measurement model with at least 2 indicators for each time point is formulated to identify measurement error variances and obtain latent variables that are purged from measurement error. In the second step, we use contrast matrices to define the latent growth…

The purpose of the study is to determine what effects explicit and systematic math intervention instruction will have on student's performance on math assessments. The study will focus on a small group of fifth grade students that have been identified as needing targeted intervention (tier 2) and intensive interventions (tier 1) through the…

This article focuses on the study of intergenerational educational mobility in Greece. The primary purpose is to represent quantitatively the transitions of individuals, in order to determine whether and to what extent the educational levels attained are influenced by parental education. The authors use data drawn from the European Union…

Indefinite symmetric matrices that are estimates of positive-definite population matrices occur in a variety of contexts such as correlation matrices computed from pairwise present missing data and multinormal based methods for discretized variables. This note describes a methodology for scaling selected off-diagonal rows and columns of such a…

There is a lack of research on the effects of outliers on the decisions about the number of factors to retain in an exploratory factor analysis, especially for outliers arising from unintended and unknowingly included subpopulations. The purpose of the present research was to investigate how outliers from an unintended and unknowingly included…

Cognitive diagnostic models (CDMs) attempt to uncover latent skills or attributes that examinees must possess in order to answer test items correctly. The DINA (deterministic input, noisy "and") model is a popular CDM that has been widely used. It is shown here that a logistic version of the model can easily be fit with standard software for…

This module was initially developed for a course in applications of mathematics in biology. The objective of this lesson is to investigate how the allele and genotypic frequencies associated with a particular gene might evolve over successive generations. The lesson will discuss how the Hardy-Weinberg model provides a basis for comparison when…

The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…

Second-order latent growth curve models (S. C. Duncan & Duncan, 1996; McArdle, 1988) can be used to study group differences in change in latent constructs. We give exact formulas for the covariance matrix of the parameter estimates and an algebraic expression for the estimation of slope differences. Formulas for calculations of the required sample…

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…

This article reports a study that investigated the effects of Q-matrix misspecifications on parameter estimates and misclassification rates for the deterministic-input, noisy "and" gate (DINA) model, which is a restricted latent class model for multiple classifications of respondents that can be useful for cognitively motivated diagnostic…

Salehi and Scheidt have derived several Wold-Cramer concordance theorems for q-variate stationary processes over discrete groups. This paper characterizes the concordance of the Wold decomposition with respect to families arising in the interpolation problem and the Cramer decomposition for non-full-rank q-variate stationary processes over certain…

Proposes a method for generalized constrained canonical correlation analysis (GCCANO) that incorporates external information on both rows and columns of data matrices. In this method, each set of variables is first decomposed into the sum of several submatrices according to the external information, and then canonical correlation analysis is…

Two models for scaling of paired comparison data are compared to the Thurstone case III model. Two goodness of fit indices are presented for each model for five data sets. The results illustrate the inability of the Thurstone model to adequately account for data when the scale includes extreme stimuli. (Author)

This study uses a Cook's distance type diagnostic statistic to identify unusual observations in a data set that unduly influence the estimation of a covariance matrix. Similar to many other deletion-type diagnostic statistics, this proposed measure is susceptible to masking or swamping effect in the presence of several unusual observations. In…