The National Assessment of Educational Progress (NAEP) is a continuing and nationally representative assessment of what this nation's students know and can do. NAEP has often been called the "gold standard" of assessments because it is developed using the best thinking of assessment and content specialists, education experts, and…

This study focused on two questions: (1) whether the types of study-aid test, or the levels of test anxiety would affect the level of performance on the test under non-anxious conditions; and (2) whether there would be any interaction effect between the types of study-aid test and the levels of anxiety under non-anxious conditions. Twelve female…

In his early exposition of path analysis, Duncan (1966) noted that the method "provides a calculus for indirect effects." Despite the interest in indirect causal effects, most users treat them as if they are population parameters and do not test whether they are statistically significant. Sobel (1982) has recently derived the asymptotic…

Some examinees' test-taking behavior may be so idiosyncratic that their scores are not comparable to the scores of more typical examinees. Appropriateness indices, which provide quantitative measures of response-pattern atypicality, can be viewed as statistics for testing a null hypothesis of normal test-taking behavior against an alternative…

Although the primary responsibility rests with the authors of articles reporting nonsignificant results to demonstrate the worth of the results by discussing the power of the tests, consumers should be prepared to conduct their own power analyses. This article demonstrates the use of power analysis for the interpretation of nonsignificant…

Compares grades awarded by 5 examination boards for 11 subjects at A levels. Uses data from the A Level Information System (ALIS) project for 1989. Finds discrepancies among boards not statistically significant. Fails to identify grading as consistently severe or lenient. (NL)

Power is an indicator of the ability of a statistical analysis to detect a phenomenon that does in fact exist. The issue of power is crucial for social science research because sample size, effects, and relationships studied tend to be small and the power of a study relates directly to the size of the effect of interest and the sample size.…

Each of the four classic multivariate analysis of variance (MANOVA) tests of statistical significance may lead a researcher to different decisions as to whether a null hypothesis should be rejected: (1) Wilks' lambda; (2) Lawley-Hotelling trace criterion; (3) Roy's greatest characteristic root criterion; and (4) Pillai's trace criterion. These…

In the educational research literature alpha, the a priori level of significance, and p, the a posteriori probability of obtaining a test statistic of at least a certain value when the null hypothesis is true, are often confused. Explanations for this confusion are offered. Paradoxically, alpha retains a prominent place in textbook discussions of…

Attempts to distill a growing technical literature on repeated-measures analysis of variance into a few simple principles for selecting an analytic technique. Argues that researchers ought not opt for a general analysis strategy when current computer technology makes it possible to select the optimal analysis technique for a given data set. (RH)

Using a Monte Carlo approach, comparison was made between traditional procedures and a multiple linear regression approach to test for differences between values of r sub 1 and r sub 2 when sample data were dependent and independent. For independent sample data, results from a z-test were compared to results from using multiple linear regression.…

This article first outlines the logic of null hypothesis testing and the problems of using it to evaluate special education research. It then presents three alternative metrics, a binomial effect size display, a relative risk ratio, and an odds ratio, that can better identify important treatment effects using illustrative data from recently…

This article compares three models that have been the foundation for approaches to the analysis of statistical significance in early childhood research--the Fisherian and the Neyman-Pearson models (both considered "classical" approaches), and the Bayesian model. The article concludes that all three models have a place in the analysis of research…

This article explains and illustrates the estimation of the power of statistical tests used to analyze data in early childhood special education research, and discusses advantages and disadvantages of various ways to increase power, such as using a directional alternate hypothesis or using a parametric, rather than nonparametric, statistical test.…

A growing controversy surrounds the strict interpretation of statistical significance tests in social research. Statistical significance tests fail in particular to provide estimates for the stability of research results. Methods that do provide such estimates are known as invariance or cross-validation procedures. Invariance analysis is largely…