An approach for modifying the results of asymptotic theory to improve the performance of statistical procedures in small to moderate sample sizes is described in the context of hypothesis testing. The method is illustrated by a series of examples. (Author)

The robustness of hypothesis tests for the correlation coefficient under varying conditions is discussed. The effects of violations of the assumptions of linearity, homoscedasticity, and kurtosis are examined. (JKS)

Statistical techniques for summarizing results from independent correlational studies are presented. The case in which only the sample correlation coefficients are available and the case in which the original paired data are available are both considered. (Author/JKS)

Two potentially useful tests for homogeneity of variance--the jackknife test and the Box test--are described and compared. Recommendations for the use of these techniques and computational examples of each are provided. (Author/JKS)

Presents an exposition of two data reduction methods--single-link and complete-link hierarchical clustering. Emphasis is on statistical techniques for evaluating the adequacy of a completed partition hierarchy and the individual partitions within the sequence. A numerical reanalysis of data illustrates the methodology. (RC)

Two forms, pure-rank and mixed-rank, of a nonparametric, general, linear model-based statistic that can be used to test several hypotheses are presented. A Monte Carlo study was used to investigate the distributional properties of these forms, and their use is discussed. (SLD)

The evaluation of competing analysis strategies based on estimator bias and variance is demonstrated using gains in standard scores and analysis of covariance procedures for quasi-experiments conforming to the fan-spread hypothesis. The findings do not lead to a uniform recommendation of either approach. (Author/JKS)

Five methods of performing pairwise multiple comparisons in repeated measures designs were investigated. Consideration of both Type I and Type II error rates found in the simulated conditions for the five procedures suggests that a Bonferroni method utilizing a separate error term for each comparison should be employed. (Author/JKS)

The paper presents a unified approach to some of the more popular nonparametric methods in current use, providing the reader with new insights by exhibiting relationships to relevant population parameters. (Author/LMO)

Six behavioral statistics textbooks listed by their publishers as "bestsellers" during 1982 were reviewed by the author. The intent was to detect the presence of and to discuss the nature of some theoretical inferential inaccuracies, misinterpretations and errors. (Author/LMO)

The regression-discontinuity design (RDD) offers the possibility of making inferences about causal effects from observations on selected groups. Data from such a design are considered to have a truncated bivariate distribution. For the RDD, maximum likelihood parameter estimation procedures and tests of hypotheses are presented. (Author/BW)

Compares three methods of analyzing pairwise treatment differences in a multi-treatment experiment via computer simulation techniques. Under the equal n condition, the robustness of the conventional Tukey Wholly Significant Difference test (WSD) to heterogeneous variances was contrasted with two alternate techniques. Under unequal n conditions,…

A method is suggested to incorporate instruction in the concept and the application of power considerations into an applied statistics course. This is based on designing one table usable for a wide range of the type of statistical tests usually introduced in such a course. (Author)

This paper investigates three methods for comparing medians rather than means in studying two independent treatment groups. The method that gave the best results is based on a normal approximation of the distribution of the sample median where the variance is estimated using results reported by Maritz and Jarrett. (Author/JAZ)

Using data from the High School and Beyond, this article presents statistical procedures to estimate the effect of dropping out of high school on cognitive achievement test scores. Each sampled dropout is matched to a student remaining in the same school. Methods for addressing the possible omission of covariates are described. (BS)