Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…

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…

Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…

In order to circumvent the influence of correlation in paired-samples and repeated measures experimental designs, researchers typically perform a one-sample Student "t" test on difference scores. That procedure entails some loss of power, because it employs N - 1 degrees of freedom instead of the 2N - 2 degrees of freedom of the…

In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…

This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…

This "What Works Clearinghouse Procedures and Standards Handbook (Version 3.0)" provides a detailed description of the standards and procedures of the What Works Clearinghouse (WWC). The remaining chapters of this Handbook are organized to take the reader through the basic steps that the WWC uses to develop a review protocol, identify…

This study is an evaluation of the behavior of the Liu-Agresti estimator of the cumulative common odds ratio when identifying differential item functioning (DIF) with polytomously scored test items using small samples. The Liu-Agresti estimator has been proposed by Penfield and Algina as a promising approach for the study of polytomous DIF but no…

This methodological brief introduces the readers to the propensity score matching method, which can be used for enhancing the validity of causal inferences in research situations involving nonexperimental design or observational research, or in situations where the benefits of an experimental design are not fully realized because of reasons beyond…

This report provides estimates of criminal incidents that occur at school. Incident-level data were obtained from the National Crime Victimization Survey (NCVS), the nation's primary source of information on criminal victimization and criminal incidents in the United States. The NCVS collects demographic information on respondents in the NCVS…

Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…

The performance was studied of five small-sample statistics--by F. M. Lord, W. Kristof, Q. McNemar, R. A. Forsyth and L. S. Feldt, and J. P. Braden--that test whether two variables measure the same trait except for measurement error. Effects of non-normality were investigated. The McNemar statistic was most powerful. (TJH)

Population invariance is an important requirement of test equating. An equating function is said to be population invariant when the choice of (sub)population used to compute the equating function does not matter. In recent studies, the extent to which equating functions are population invariant is typically addressed in terms of practical…

This paper discusses the sample size problem and four factors affecting its solution: significance level, statistical power, analysis procedure, and effect size. The interrelationship between these factors is discussed and demonstrated by calculating minimal sample size requirements for a variety of research conditions. (Author)

Determination of statistical power for analysis of variance procedures requires five elements: (1) significance level; (2) effect size; (3) number of means; (4) error variance; and (5) sample size. Significance levels are traditionally chosen to be 0.5, .01, or .001. Effect size is not discussed in this paper. The number of means is determined by…