Since the mid-1960s, when illicit drug use burgeoned in the normal youth population, substance use by American young people has proven to be a rapidly changing phenomenon. Smoking, drinking, and illicit drug use are leading causes of morbidity and mortality, both during adolescence as well as later in life. How vigorously the nation responds to…

Given the increased risk factors in the transition from middle school to high school, this study tracked academic and school discipline records for students receiving general and special education services as they transitioned from Grade 8 to Grade 9. The authors employed analysis of variance and structural equation modeling to determine the…

This paper begins with a general discussion of statistical significance, effect size, and power analysis; and concludes by extending the discussion to the multivariate case (MANOVA). Historically, traditional statistical significance testing has guided researchers' thinking about the meaningfulness of their data. The use of significance testing…

Problems inherent in relying solely on statistical significance testing as a means of data interpretation are reviewed. The biggest problem with statistical significance testing is that researchers have used the results of this testing to ascribe importance or meaning to their studies where such meaning often does not exist. Often researchers…

The original nine programs for semantic differential analysis have been condensed into three programs which have been further refined and augmented. They yield: (1) means, standard deviations, and standard errors for each subscale on each concept; (2) Evaluation, Potency, and Activity (EPA) means, standard deviations, and standard errors; (3)…

Population invariance is an important requirement of test equating. An equating function is said to be population invariant when the choice of (sub)population used to compute the equating function does not matter. In recent studies, the extent to which equating functions are population invariant is typically addressed in terms of practical…

Researchers increasingly recognize that significance tests are limited in their ability to inform scientific practice. Common errors in interpreting significance tests and three strategies for augmenting the interpretation of significance test results are illustrated. The first strategy for augmenting the interpretation of significance tests…

Use of "special" orthonormal mean contrasts and mean contrast variances can help educational researchers interpret a wide variety of repeated measures data. Most statistical packages allow educational researchers to test for differences across repeated measures using both the univariate mixed model F test and a multivariate test.…

Power is an indicator of the ability of a statistical analysis to detect a phenomenon that does in fact exist. The issue of power is crucial for social science research because sample size, effects, and relationships studied tend to be small and the power of a study relates directly to the size of the effect of interest and the sample size.…

A fundamental fact of the analysis of variance statistical procedure is that if the omnibus F test of an effect is significant, then there exists at least one contrast of that effect that will be significantly different from zero according to the S-method of Scheffe. The caveat to this rule is that the significant contrast(s) may not be of any…

Two types of statistical analyses of rating scale data are discussed. An example, with its accompanying mathematical calculations for each type, is presented; and the advantages and disadvantages of each method are compared. It is judged that the little-known and seldom-used Kolmogorov-Smirnov one-sample test should be reexamined because of its…

The implications of data from a review of ten years of the American Educational Research Journal (AERJ) indicating that random sampling is rare and that there is increased use of quasi-experimental designs lacking in random assignment are considered. It is suggested that tests of significance could be abandoned or at least placed in a subsidiary…

The problem of determing how many significant discriminant functions are present in a given data set for a one-way, fixed-effects multivariate analysis of variance design is studied using a Monte Carlo procedure. A variety of procedures, including the popular partitioned-U procedure, are compared with respect to their Type I error rates and power…