The present investigation developed power curves for two parametric and two nonparametric procedures for testing the equality of population variances. Both normal and non-normal distributions were considered for the two group design with equal and unequal sample frequencies. The results indicated that when population distributions differed only in…

Monte Carlo studies explored the sampling characteristics of Cohen's d and three approximations to Cohen's d when used as average effect size measures in meta-analysis. Reviews of 10, 100, and 500 studies (M) were simulated, with degrees of freedom (df) varied in seven steps from 8 to 58. In a two independent groups design, samples were obtained…

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

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 results obtained from two basic types of pre-equatings of tests were compared: the item response theory (IRT) pre-equating and section pre-equating (SPE). The simulated data were generated from a modified three-parameter logistic model with a constant guessing parameter. Responses of two replication samples of 3000 examinees on two 72-item…

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…

This study examined how four commonly used test equating procedures (linear, equipercentile, Rasch Model, and three-parameter) would respond to situations in which the properties or the two tests being equated were different. Data for two tests plus an external anchor test were generated from a three parameter model in which mean test differences…

The purpose of this paper is to present two new alternative methods to the current goodness of fit methodology. With the increase use of computerized adaptive test (CAT), the ability to determine the accuracy of calibrated item parameter estimates is paramount. The first method applies a normalizing transformation to the logistic residuals to make…

The TESTFACT computer program and full-information factor analysis of test items were used in a computer simulation conducted to correct for the guessing effect. Full-information factor analysis also corrects for omitted items. The present version of TESTFACT handles up to five factors and 150 items. A preliminary smoothing of the tetrachoric…

Though item bias statistics are widely recommended for use in test development and analysis, problems arise in their interpretation. This research evaluates logistic test models and computer simulation methods for providing a frame of reference for interpreting item bias statistics. Specifically, the intent was to produce simulated sampling…

Item analysis data fitting the normal ogive model were simulated in order to investigate the problems encountered when applying the three-parameter logistic model. Binary item tests containing 10 and 35 items were created, and Monte Carlo methods simulated the responses of 2,000 and 500 examinees. Item parameters were obtained using Logist 5.…

The purpose of this study was to investigate the effect of using multidimensional items in a computer adaptive test (CAT) setting which assumes a unidimensional item response theory (IRT) framework. Previous research has suggested that the composite of multidimensional abilities being estimated by a unidimensional IRT model is not constant…