Regression mixture models are a statistical approach used for estimating heterogeneity in effects. This study investigates the impact of sample size on regression mixture's ability to produce "stable" results. Monte Carlo simulations and analysis of resamples from an application data set were used to illustrate the types of problems that…

Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the…

Multivariate analysis of variance (MANOVA) is widely used in educational research to compare means on multiple dependent variables across groups. Researchers faced with the problem of missing data often use multiple imputation of values in place of the missing observations. This study compares the performance of 2 methods for combining p values in…

Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…

Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

Classical methods for detecting outliers deal with continuous variables. These methods are not readily applicable to categorical data, such as incorrect/correct scores (0/1) and ordered rating scale scores (e.g., 0,..., 4) typical of multi-item tests and questionnaires. This study proposes two definitions of outlier scores suited for categorical…

This paper examines some of the problems that arise when conducting multivariate analyses with incomplete data. The literature on the effectiveness of several missing data procedures (MDP) is summarized. The most widely used MDPs are: (1) listwise deletion; (2) pairwise deletion; (3) variable mean; (4) correlational methods. No MDP should be used…

Discusses the problem of dichotomous-dependent variables in regression analysis in student attrition studies. Proposes a new method as an alternative to regression analysis. (Author/RC)

Problems associated with the use of analysis of covariance (ANCOVA) as a statistical control technique are explained. Three problems relate to the use of "OVA" methods (analysis of variance, analysis of covariance, multivariate analysis of variance, and multivariate analysis of covariance) in general. These are: (1) the wasting of information when…

The term "ipsative" refers to measurement based on intra-individual comparisons. The research literature in the social sciences contains many cautions about using ipsative data in multivariate analysis. The purpose of this paper is to identify the problems associated with the multivariate and regression analyses of ipsative data and to…

Batterers with access to firearms present a serious lethal threat to their partners. The purpose of this exploratory study is to estimate the prevalence of and risk markers for gun possession among Massachusetts men enrolled in batterer intervention programs. The authors found that 1.8% of the men reported having a gun in or around their home.…

Asserts that traditional approaches to multivariate analysis, including standard linear regression techniques, ignore the special character of count data. Explicates three suitable alternatives to standard regression techniques, a simple Poisson regression, a modified Poisson regression, and a negative binomial model. (MJP)

This monograph covers the theory, application, and interpretation of both descriptive and inferential statistical techniques in institutional research. Each chapter opens with a hypothetical case study, which is used to illustrate the application of one or more statistical procedures to typical research questions. Chapter 2 covers the comparison…