Effect sizes are important because they are an accessible way to indicate the practical importance of observed associations or differences. Standardized mean difference (SMD) effect sizes, such as Cohen's d, are widely used in education and the social sciences -- in part because they are relatively easy to calculate. However, SMD effect sizes…

The purpose of this study is to look closely at how aspects of instructional leadership, and organizational learning affect the quality of madrasah in improving the quality of graduate the state madrasah aliyah. The experiment was conducted using a quantitative approach with descriptive and inferential methods, in inferential methods used…

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the…

Discussions of efficiency among Historically Black Colleges and Universities (HBCUs) are often missing in academic conversations. This article seeks to assess efficiency of individual HBCUs using Data Envelopment Analysis (DEA), a non-parametric technique that can synthesize multiple inputs and outputs to determine a single efficiency score for…

Relative to given scale properties of each of two paired variables, a program for identification and computation of the following indices of relationship is provided: phi, Spearman rank order, Kendall's Tau, Pearson's product moment, biserial, and point biserial. (Author/RC)

Formulas and a FORTRAN program for computing Kendall's Tau as well as a generalized Spearman rho coefficient from ordered contingency tables are described. (Author)

Illustrates a simple nonparametric alternative that can be used to test a hypothesis that two proximity matrices on the same set of variables or objects reflect a similar pattern of high and low entries. (RC)

This paper presents an empirical analysis of similarities and differences between two statistics, G and Phi, which treat genuinely dichotomous data. These results can aid researchers in selecting between these two statistics and in evaluating results from the use of one v the other. (Author)

Treats the problem of testing an ordered hypothesis based on the ranks of the data. Statistical procedures for the randomized block design with more than one observation per cell are derived. Multiple comparisions and estimation procedures are included. (Author/RC)

The problem of objectively comparing two independently determined partitions of N objects or variables is discussed. A similarity measure based on the simple matching coefficient is defined and related to previously suggested measures. (Author/JKS)

Defining population diversity as the distribution along a continuum of homogeneity to heterogeneity with respect to one or more variables, measures are described with variance-based interpretations which can be applied to qualitative data. It is possible to use these statistics to define relationships in multivariate distributions. (Author/CTM)

Examines the similarity between the coordinates which resulted when correlations were used as similarity measures and the factor loadings obtained by factor analyzing the same correlation matrix. Real data, a set of error free data, and some computer generated data containing deliberately introduced sampling error are analyzed. (RC)

A strategy for comparing two sets of results (one based upon early childhood recollections (ECR) and another upon video taped (VT) group behavior) from the Perceptual Characteristics Rating Scale was developed. The null distribution of the mean deviation was estimated by randomly matching an ECR response vector with a VT response vector. To…

STATGRAPHICS, a statistical package written for the IBM PC/XT/AT, is reviewed. In addition to superb graphics, STATGRAPHICS is unequalled in time series procedures, quality control, linear programming, and other mathematical procedures. The modules for regression analysis, categorical data analysis, and nonparametric analysis are good, but contain…