Research designs that include planned missing data are gaining popularity in applied education research. These methods have traditionally relied on introducing missingness into data collections using the missing completely at random (MCAR) mechanism. This study assesses whether planned missingness can also be implemented when data are instead…

Investigates the question of under what conditions can one infer that some observed relationship between two empirical variables reflects more than that they are both indicants of the same construct. (RC)

Three problems with stepwise research methods are explored. Computer packages may use incorrect degrees of freedom in stepwise computations. In addition, stepwise methods do not identify correctly the best variable set of a given size. A third problem is that stepwise methods tend to capitalize on sampling error. (SLD)

The use of meta-analysis to resolve issues in the fields of organizational behavior and human resources management was reviewed by coding 35 studies on 21 methodological variables. Results illustrate the tremendous variability in how researchers apply meta-analysis. Suggestions are provided for correctly using meta-analysis. (SLD)

In this paper, tables for the appropriate sample sizes are presented and discussed in the context that the determination of the effect size must precede the determination of the sample size. (Author/PN)

The purpose of this study was to determise the relative loss in statistical power of traditional methods of analysis when response-shift bias is present. Five methods of analysis (posttest scores only; postminus pretests; postminus retrospective pretest; postcovaried by pretest; postcovaried by retrospective pretest) were compared. (Author/BW)

This study compares multitrait-multimethod analyses (MTMM) performed on items and factor scores derived from the items. Based upon this demonstration, researchers are encouraged to conduct a preliminary factor analysis before analyzing MTMM data whenever there is a doubt about the underlying trait structure. (Author/PN)