In this paper, the statistical significance of the contribution of variables to the principal components in principal components analysis (PCA) is assessed nonparametrically by the use of permutation tests. We compare a new strategy to a strategy used in previous research consisting of permuting the columns (variables) of a data matrix…

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…

Researchers conducting studies involving individuals with exceptionalities are often prevented from involving large numbers of participants in their study samples. When this is the case, some say significant correlations are likely to replicate because the relation between two variables must be robust enough to be detected even with low…

Designing for the needs of people with impairments has rarely been a significant feature of urban planning theory and education. Given the role of urban planners as shapers of the built environment and public policy, the prevalence of negative and misinformed attitudes among planners toward impaired populations has been highlighted as requiring…

This NCEE Technical Methods report examines how to address the problem of missing data in the analysis of data in Randomized Controlled Trials (RCTs) of educational interventions, with a particular focus on the common educational situation in which groups of students such as entire classrooms or schools are randomized. Missing outcome data are a…

A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects. This…

A modification of the SIBTEST procedure to assess differential item functioning (DIF) for two-dimensional test data (i.e., data for tests where two intended abilities are tapped by test items) is described. A small simulation study is carried out to assess the performance of the modified SIBTEST to detect DIF in such two-dimensional data. The…

The level of standardized effect sizes obtained by chance and the use of significance tests to guard against spuriously high standardized effect sizes were studied. The concept of the "protected effect size" is also introduced. Monte Carlo methods were used to generate data for the study using random normal deviates as the basis for sample means…

Two strategies, derived from J. P. Schaffer (1986), were compared as tests of significance for a complete set of planned orthogonal contrasts. The procedures both maintain an experimentwise error rate at or below alpha, but differ in the manner in which they test the contrast with the largest observed difference. One approach proceeds directly to…

Two types of qualitative dependent variables are presented for use in counseling research: choices from an unordered set of categorical alternatives and ordered, categorical counseling outcomes. To investigate school choice behavior, the conditional logit model and analysis are introduced. The conditional logit model can include the attributes of…

This paper suggests that statistical significance testing and effect size are two sides of the same coin; they complement each other, but do not substitute for one another. Good research practice requires that both should be taken into consideration to make sound quantitative decisions. A Monte Carlo simulation experiment was conducted, and a…

Five methods for testing the hypothesis of independence between two sets of variates were compared through simulation. Results indicate that two new methods, based on robust measures reflecting the linear association between two random variables, provide reasonably accurate control over Type I errors. Drawbacks to rank-based methods are discussed.…

This research explored the degree to which group sizes can differ before the robustness of analysis of variance (ANOVA) and analysis of covariance (ANCOVA) are jeopardized. Monte Carlo methodology was used, allowing for the experimental investigation of potential threats to robustness under conditions common to researchers in education. The…

Formulae for estimating individual rater reliabilities from analysis of treatment effects are presented and evaluated. Monte Carlo methods illustrate the formulae. Results indicate that large sample sizes, large true treatment effects, and large differences in the actual reliabilities of raters are required for the approach to be useful. (SLD)