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Multivariate permutation tests are described and studied which may be profitably substituted for Hotelling's one-sample P test in situations commonly arising in behavioral science research. These tests (a) may be computed even when the number of variables exceeds the number of subjects, (b) are distribution-free, (c) may be tailored for sensitivity to(More)
This study describes an investigation of the intellectual property policies of 42 public and private Carnegie Doctoral Research – Extensive Universities. Using a policy analysis framework based on earlier work by Lape (1992) and Packard (2001), policy differences between public and private universities and policy changes across time were analyzed and(More)
Introduction  As the use of multilevel models has expanded into new areas, questions have emerged concerning how well these models work under various design conditions  Sample size at each level of analysis continues to be an important design condition in multilevel modeling Background
This article uses meta-analyses published in Psychological Bulletin from 1995 to 2005 to describe meta-analyses in psychology, including examination of statistical power, Type I errors resulting from multiple comparisons, and model choice. Retrospective power estimates indicated that univariate categorical and continuous moderators, individual moderators in(More)
KEYWORDS: meta-analysis, robustness, effect size, Monte Carlo study With the growing popularity of meta-analytic techniques to analyze and synthesize results across sets of empirical studies, have come concerns about the sensitivity of traditional tests in meta-analysis to violations of assumptions. This is particularly distressing because the tenability of(More)
Sample size at each level is important to consider when estimating multilevel models. Although general sample size guidelines have been suggested, the nature of social science survey research (e.g., large number of level-2 units with few individuals per unit) often makes such recommendations difficult to follow. This Monte Carlo study focuses on the(More)
Effect sizes are useful statistics that complement null hypothesis testing and confidence interval estimation. Because traditional indices of effect size are sensitive to violations of distributional assumptions, many robust effect size indices have been proposed and described in the methodological literature. The macro described in this paper computes the(More)
Although statistical power is often considered in the design of primary research studies, it is rarely considered in meta-analysis. Background and guidelines are provided for conducting power analysis in meta-analysis, followed by the presentation of a SAS macro that calculates power using the methods described by Hedges and Pigott (2001, 2004). Several(More)