Adjustment methods such as propensity scores and analysis of covariance are often used for estimating treatment effects in nonexperimental data. Shadish, Clark, and Steiner used a within-study comparison to test how well these adjustments work in practice. They randomly assigned participating students to a randomized or nonrandomized experiment.…

The amount of variance accounted for by treatment can be estimated with omega squared or with the squared multiple correlation coefficient. Monte Carlo methods were employed to compare omega squared, the squared multiple correlation coefficient, and the squared multiple correlation coefficient to which a shrinkage formula had been applied, in…

Examines assumptions underlying the employment of group means in communication research. Suggests a sample mean cannot be assumed to be a "good" statistic when the response vector represents different individuals' outcomes versus different outcomes of an individual. Notes implications for communication research. (SR)

Evaluations involving nonrandom assignment to treatment or control groups are vulnerable to an accidental or intentional confounding of a selection effect with the treatment effect. Two techniques, discriminant analysis and base expectancy analysis, permit separate estimation of the selection and treatment effects in the final results. (Author/CTM)

The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model, and principal axes factor analyses were performed. (Author/LMO)

A normally distributed data set of 1,000 values--ranging from 50 to 150, with a mean of 50 and a standard deviation of 20--was created in order to evaluate the bootstrap method of repeated random sampling. Nine bootstrap samples of N=10 and nine more bootstrap samples of N=25 were randomly selected. One thousand random samples were selected from…

Student's empirical sampling approach is used to assess the magnitude of the sampling errors of statistics describing a recursive causal model. The data were gathered with four complex sample designs commonly used in educational surveys. Jackknife and half-sample error estimates are applied to the data. (Author/CTM)

The average design effects for statistics estimated from the base-year National Longitudinal Study data are presented. Attempts to partition the effects into those due to stratification, clustering, and unequal weighting are discussed. The expected increases in subpopulation sample sizes due to oversampling are calculated and compared with the…

Longitudinal measures of change are the most important kinds of estimates being produced from the National Longitudinal Study of the High School Class of 1972 (NLS). Several topics are presented in this report, most of which build on previous variance components analyses. The major areas covered are effects of stratification and clustering,…

The purpose of this study was to empirically determine the effects of quantified violations of the underlying assumptions of parametric statistical tests commonly used in educational research, namely the correlation coefficient (r) and the t test. The effects of heterogeneity of variance, nonnormality, and nonlinear transformations of scales were…

The sampling of teachers for nationwide surveys offers a challenging endeavor in obtaining a representative and adequate sample to truly represent opinions of the teachers. Ten national surveys of public school teachers conducted between 1980 and 1985 are presented with respect to their sampling design and procedures. Concepts and theoretical…