Research hypotheses versus statistical hypotheses, null hypotheses and alternative hypotheses, and statistical significance versus practical significance are described and illustrated. (CP)

A multiple-choice achievement test was constructed in which both cognitive level and degree of abstractness were controlled in test items. By controlling both dimensions, researchers hoped that the variance in achievement scores of earlier research could be accounted for. Results of testing education majors are discussed. (Author/MT)

The use of measures of magnitude of effect has been advocated as a way to go beyond statistical tests of significance and to identify effects of a practical size. They have been used in meta-analysis to combine results of different studies. Describes problems associated with measures of magnitude of effect (particularly study size) and…

A recent study (Blair and Higgins, 1980) indicated a power advantage for the Wilcoxon W Test over student's t-test when calculated from a common mixed-normal sample. Results of the present study indicate that the t-test corrected for outliers shows a superior power curve to the Wilcoxon W.

Occupational theory research has been associated with low statistical power and a high rate of Type II errors. To increase power, a procedure involving the partitioning of the decision region into three sections, based on the decision-theory approach to significance testing, is proposed. (SK)

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,…

Two psychological experiments--Anderson and Shanteau (1970), Berkowitz and LePage (1967)--are reanalyzed to present the problem of the relative importance of low Type 1 error probability and high power when answering a research question by testing several statistical hypotheses. (Author/PN)

Methods of assessing effect size and the flows that limit their usefulness are discussed. The various statistical procedures for estimating variance accounted for are based on different statistical models producing sharply differing results. The methods reflect too greatly the particular study characteristics and hence have limited…

Hintzman's 1980 attack on certain analyses in memory research is based on doubtful presumptions, namely, that contingency tables are inherently suspect as evidence for or against scientific conclusions and that pressing this logical argument is in some way an acceptable substitute for empirically examining the conclusions in question. (Author)

There are difficulties in expressing effect sizes on a common metric when some studies use transformed scales to express group differences, or use factorial designs or covariance adjustments to obtain a reduced error term. A common metric on which effect sizes may be standardized is described. (Author/RL)

It is shown how partial covariance, part and partial correlation, and regression weights can be estimated and tested for significance by means of a factor analytic model. Comparable partial covariance, correlations, and regression weights have identical significance tests. (Author)

Argues that a broad dimension of useful experiments would be suggested if the field supplemented its current research strategy with a second strategy focused more explicitly on the extension of generality. (HOD)

The Guttman scale is discussed from the viewpoint of errors in response patterns. The errors are assumed to be distributed as a binomial. A double-barreled significance test is suggested having two probabilities: high probability and low probability. (Author)