Effectiveness of jackknife methods in reducing bias in estimation of the log-1 autocorrelation parameter p1 was evaluated through a Monte Carlo study using sample sizes ranging from 6 to 500. These estimates appear less biased in the small sample case than many that have been investigated recently. (SLD)

The predicted scores produced by regression with (1) single best predictor, (2) two best predictors, (3) all predictors with observed values, and (4) all predictors with or without observed values were compared with variable means as estimates of missing values. The study was conducted in a simulation mode on nx8 data matrices using various levels…

Using computer simulation data, the effect of a single global outlier in two-group classification analysis was explored in terms of the outcome variables of change in classification results (PCHNG), change in misclassification rate (MISDIF), and change in precision of misclassification rate estimation. The precision of misclassification rate…

Using a Monte Carlo simulation, a bootstrap procedure was evaluated for setting a confidence interval on the unrestricted population correlation (rho) assuming various degrees of incomplete truncation on the predictor. Sample size was the most important factor in determining accuracy and stability. Sample size should be at least 50. (SLD)

The influence of sample size (N) and model parsimony on a set of 22 goodness of fit indices was investigated, including those typically used in confirmatory factor analysis and some recently developed indices. For sample data simulated from 2 known population data structures, values for 6 of 22 fit indices were reasonably independent of N and were…

An investigation of the effects of randomly missing data in two-predictor regression analyses is described. The differences in the effectiveness of five common treatments of missing data on estimates of R-squared values and each of the two standardized regression weights is also investigated. Bootstrap sample sizes of 50, 100, and 200 were drawn…

Investigates the BILOG computer program's ability to recover known item parameters for different numbers of items, examinees, and variances of the prior distributions of discrimination parameters for the two-parameter logistic item-response theory model. For samples of at least 250 examinees and 15 items, simulation results support using BILOG.…

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item and ability parameters through two joint and two marginal Bayesian procedures. Marginal procedures yielded smaller root mean square differences for item and ability, but results for larger sample size and test length were similar.…

The standard error (SE) of correlations adjusted for selection with commonly used formulas was investigated. The study provides large-sample approximations of SE using the Pearson-Lawley three-variable correction formula, examines the SE under specific conditions, and compares various estimates of SEs under direct and indirect selection. (TJH)

This study investigates parameter estimation under the simple linear regression model for situations in which the underlying assumptions of ordinary least squares estimation are untenable. Classical nonparametric estimation methods are directly compared against some robust estimation methods for conditions in which varying degrees of outliers are…

This Monte Carlo study examines whether, given various numbers of variables, treatments, and sample sizes, in a one-way multivariate analysis of variance, Type I error rates of the test approximations provided by the BMDP program, the Statistical Analysis System (SAS), and the Statistical Package for the Social Sciences (SPSS) for Roy's largest…

There are times in survey research when missing values need to be estimated. The robustness of four variations of regression and substitution by mean methods was examined using a 3x3x4 factorial design. The regression variations included in the study were: (1) regression using a single best predictor; (2) two best predictors; (3) all available…

Current omnibus procedures for the analysis of interaction effects in repeated measures designs which contain a grouping variable are known to be nonrobust to violations of multisample sphericity, particularly when group sizes are unequal. An alternative approach is to formulate a comprehensive set of contrasts on the data which probe the specific…

A Monte Carlo study was done to determine the adequate sample size for quasi-experimental regression studies, which compare regression lines for two groups and estimate their point of intersection. Populations of 1,000 subjects in each of two groups were constructed (using random normal deviates) to yield equivalent regression lines of opposite…

The impact of capitalizing on chance in item selection on the accuracy of test information functions was studied through simulation, focusing on examinee sample size in item calibration and the ratio of item bank size to test length. (SLD)