Many interactions are found with categorical variables but few with continuous variables, suggesting that, from a mathematical point of view, investigating interactions with continuous variables is less powerful than with categorical variables. This issue is analyzed from three other points of view: study design, measurement of the independent…

J. Frass and I. Newman (2000) proposed a hypothesis testing procedure that incorporated the following three key elements: (1) the establishment of a practical significance value; (2) the construction of a non-nil null hypothesis that incorporated the practical significance value; and (3) statistical testing of the non-nil null hypothesis with a…

Statistical significance and practical significance can be considered jointly through the use of non-nil null hypotheses that are based on values deemed to be practically significant. When examining differences between the means of two groups, researchers can use a randomization test or an independent t test. The issue addressed in this paper is…

This paper provides examples of how one can use the research issue and the relationships between qualitative and quantitative research as a frame for instructing students and judging the quality of research. The emphasis is on validity estimates, also called legitimization techniques, with attention to the idea of a qualitative-quantitative…

The major concern for any research model, whether disproportionate or not, is the research question and how well that question is reflected by the model. Three "exact solutions" for disproportional situations, the hierarchial, unadjusted main effects, and fitting constant methods, are discussed in terms of the research question that each…

Fifteen examples using different formulas for calculating degrees of freedom for power analysis of multiple regression designs worked out by Cohen are presented, along with a more general formula for calculating such degrees of freedom. (Author/JKS)

When investigating differences between two sets of scores, the t test is appropriate. If the two sets of data are from two groups of subjects, then the independent t test is appropriate. If the two sets are from the same subjects, the dependent t test is required. In this paper, the authors describe the use of a third test when part of a data set…

Presents situations in which researchers can use the general linear model to uncover reasons for discrepant effect-size results of meta-analysis of similar studies. Situations include similarly labeled treatments or participants differing in important ways, treatment effectiveness varying by subject aptitude or situational variables, research…

A new method for evaluating model fit that is easy to use and interpret is presented. The new method, which uses a binomial test of the number of hypotheses (paths) in a model that are supported by the data, has heuristic value when considering problems associated with other goodness-of-fit measures. An application of the binomial test as a…

Problems associated with the analysis of data collected using the Solomon Four Group Design are discussed. The design includes an experimental group and a control group that have been pretested and posttested, and an experimental and a control group that have been posttested only. A sample problem is approached in three different ways. First, the…

Based on the assumption that inferential statistics can make the operant conditioner more sensitive to possible significant relationships, regressions models were developed to test the statistical significance between slopes and Y intercepts of the experimental and control group subjects. These results were then compared to the traditional operant…