All parametric statistical analyses have certain assumptions about the data that must be met reasonably to warrant the use of a given analysis. Distributional normality, for example, is a common assumption. There is a variety of ways that data in a distribution may detract from normality, but one common problem is the presence of outliers. Many…

Results of a study of repeated measures stepwise multiple comparison procedures indicate that multiple range procedures modified according to Duncan's (1975) method and employing nonpooled omnibus or pairwise stepwise procedures are robust to violations of the multisample sphericity assumption and are typically more powerful than the usual range…

Developed a sample-based nonanalytical degrees-of-freedom correction factor for situations sampling both subjects and conditions with measurement data departing from essentially parallel form. Assessed the application of this correction factor through a simulation study involving data sets with a range of design characteristics and manifesting…

Estimated empirical Type I error rate and power rate for three procedures for analyzing multivariate repeated measures designs: (1) the doubly multivariate model; (2) the Welch-James multivariate solution (H. Keselman, M. Carriere, a nd L. Lix, 1993); and (3) the multivariate version of the modified Brown-Forsythe procedure (M. Brown and A.…

Argues that informetrics needs a rigorous mathematical basis and that informetric processes can be adequately describes within a standard probabilistic framework with stochastic modeling offering a more productive approach than other methods. Highlights include Lotka's Law; robustness and multiauthorship; and resilience and the random component.…

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

Drug studies are often cited as the best exemplars of evaluation design. However, many of these studies are seriously biased in favor of positive findings for the drugs evaluated, even to the point where dangerous effects are hidden. In spite of using randomized designs and double blinding, drug companies have found ways of producing the results…

The term "intervention validity" refers to the extent to which assessment results can be used to guide the selection of interventions and evaluation of outcomes. In this article, the authors review the defining attributes of rating scales that distinguish them from other assessment tools, assumptions regarding the use of rating scales to…

This report describes work using nationally representative 2005 data from the School Nutrition Dietary Assessment-III (SNDA-III) study to develop a simulation model to predict the potential implications of changes in policies or practices related to school meals and school food environments. The model focuses on three domains of outcomes: (1) the…

This paper reports on a study conducted to investigate the consistency of the results between 2 approaches to estimating school effectiveness through value-added modeling. Estimates of school effects from the layered model employing item response theory (IRT) scaled data are compared to estimates derived from a discrete growth model based on the…

The aim of the National Numeracy Strategy is to raise standards in numeracy. Strong evidence for its success has, however, been lacking: most of the available data come from performance on National Test assessments administered in schools or from Ofsted reports, and is vulnerable to suggestions of bias. An opportunistic analysis of data from a…

Throughout classrooms in the United States there appears to have been a general watering down of academic standards. The percentages of "A" and "B" grades have risen, and at some schools, the percentage of grades of "C" or lower has plummeted. Numerous scholarly articles about grade inflation discuss the extent,…

Classic parametric statistical significance tests, such as analysis of variance and least squares regression, are widely used by researchers in many disciplines, including psychology. For classic parametric tests to produce accurate results, the assumptions underlying them (e.g., normality and homoscedasticity) must be satisfied. These assumptions…

Studies of college attrition typically assume that all attrition is permanent. We use data from the 1990/94 Beginning Postsecondary Survey to distinguish between long-term dropout and short-term stopout behavior in order to test that assumption. We find significant differences between those who stop out and those who drop out in the first year.…

This article addresses ethical dilemmas experienced by street-level research and evaluation workers recruiting and gathering data in community-based research projects. The authors focus on a subgroup of street-level research workers, whom they call research extenders (REs), employed because they share important characteristics with the target…