Multivariate analysis of variance (MANOVA) is a statistical procedure commonly used in fields such as education and psychology. However, MANOVA's popularity may actually be for the wrong reasons. The large majority of published research using MANOVA focus on univariate research questions rather than on the multivariate questions that MANOVA is…

Multilevel modeling (MLM) is a statistical technique for analyzing clustered data. Despite its long history, the technique and accompanying computer programs are rapidly evolving. Given the complexity of multilevel models, it is crucial for researchers to provide complete and transparent descriptions of the data, statistical analyses, and results.…

In education settings, treatments are often non-randomly assigned to clusters, such as schools or classrooms, while outcomes are measured for students. This research design is called the clustered observational study (COS). We examine the consequences of common support violations in the COS context. Common support violations occur when the…

Multivariate analysis of variance (MANOVA) is a statistical method used to examine group differences on multiple outcomes. This article reports results of a review of MANOVA in gifted education journals between 2011 and 2017 (N = 56). Findings suggest a number of conceptual and procedural misunderstandings about the nature of MANOVA and its…

In education research, small samples are common because of financial limitations, logistical challenges, or exploratory studies. With small samples, statistical principles on which researchers rely do not hold, leading to trust issues with model estimates and possible replication issues when scaling up. Researchers are generally aware of such…

Multilevel models are often used to evaluate hypotheses about relations among constructs when data are nested within clusters (Raudenbush & Bryk, 2002), although alternative approaches are available when analyzing nested data (Binder & Roberts, 2003; Sterba, 2009). The overarching goal of this article is to suggest when it is appropriate…

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…

When data are collected via anonymous Internet surveys, particularly under conditions of obligatory participation (such as with student samples), data quality can be a concern. However, little guidance exists in the published literature regarding techniques for detecting careless responses. Previously several potential approaches have been…

The use of multivariate statistics in behavioral research is investigated, with emphasis on the reasons why multivariate methods can be so important. The concepts of testwise and experimentwise error are explained, and it is noted that multivariate methods can be used to control the inflation of experimentwise Type I error. It is also noted that…

Examines the prevalence of inflated Type I error in counseling research and recommends wider use of multivariate statistics to correct the problem. Type I error becomes inflated beyond acceptable levels when researchers perform individual univariate statistics on each of several dependent variables within a single project. (Author)

Research with couples requires measurement and data analytic techniques extending beyond those typically used with individuals. Measurement issues in couples' research that influence subsequent approaches to data analysis are reviewed, with emphasis on issues of nonindependence in couples' data. Univariate and multivariate analyses of…

Although it is widely known that special assumptions are needed for univariate analysis of repeated measures data, researchers seldom examine their data for violation of these assumptions. This paper reviews ways in which repeated measures analyses are usually handled and describes limitations of these methods. A design with two within subject…

The present article reviews the procedures that have been developed for measuring the reliability of human observers' judgments when making direct observations of behavior. These include the percentage of agreement, Cohen's Kappa, phi, and univariate and multivariate agreement measures that are based on quasi-equiprobability and quasi-independence…

Provides a nontechnical explanation of the family of multivariate statistical techniques known as multidimensional scaling (MDS). Explains the purpose of MDS, and the advantages of using these techniques in the study of musical perception. Discusses two approaches to the interpretation of MDS solutions. Lists examples of musical studies using MDS.…

Recognizes some of the limitations of the field of behavioral genetics, but argues that the methods employed in multivariate behavior genetics and developmental behavior genetics have become the dominant paradigms in the field. (MDM)