The analysis of variance (ANOVA) is a frequently used statistical procedure by which the equality of more than two population means can be tested without inflating the Type I error rate (D. Hinkle, W. Wiersma, and S. Jurs, 1998). Fixed-, random-, and mixed-effects ANOVA models are each capable of yielding interesting and useful results when…

Analysis of variance (ANOVA) designs typically use what is referred to as crossed design to test for differences between means of groups. In a balanced, or crossed, one-way ANOVA, each student (unit of analysis) would have a score in each of the experimental conditions. In a two-way design, the analysis is considered crossed if each level from one…

Finds that although composite ANOVA models explain less that 1% of total variance, implying very small and subtle effects, analysis provides strong evidence that anomalies are statistically robust. (Author/CCM)

An approach to the analysis of an aptitude-treatment-interaction (ATI) design in which the treatment groups are based on an underlying factorial structure is described and illustrated. The approach emphasizes description with point and interval estimation. The example design considered consisted of two nominal treatment variables and one interval…

The level of discourse theory was empirically tested to determine its usefulness to researchers in selecting independent variables for population and subpopulation models of leisure participation. Recommendations for combining social aggregate and social action independent variables in population and subpopulation participation models are…

As an extension of B. Thompson's 1998 invited address to the American Educational Research Association, this paper cites two additional common faux pas in research methodology and explores some research issues for the future. These two errors in methodology are the use of univariate analyses in the presence of multiple outcome variables (with the…

The various costs of Type I and Type II errors of inference from data are discussed. Six methods for minimizing each error type are presented, which may be employed even after data collection for Type I and which minimizes Type II errors by a study design and analytical means combination. (Author/CM)

Examines unresolved problems and future prospects for research concerning school quality. Asserts that the proportion of variance among factors such as, school system, school type, grade levels, individual schools, and learning groups makes consideration of the schools as a homogenous whole doubtful. Includes numerous statistical tables and…

Multivariate analytic techniques offer useful research methods that permit the experiential educator to test theoretical models, analyze the effects of several variables acting together, and predict the effects of one set of variables upon another set of variables. Several of these techniques are discussed, including analysis of variance, multiple…