Simple noniterative estimators of the polyserial correlation coefficient are developed by exploiting a general relationship between the polyserial correlation and the point polyserial correlation to give extensions of the biserial estimators of K. Pearson (1909), H. E. Brogden (1949), and F. M. Lord (1963) to the multicategory setting. (SLD)

The generalized graded unfolding model (GGUM) (J. Roberts, J. Donoghue, and J. Laughlin, 1998) is an item response theory model designed to analyze binary or graded responses that are based on a proximity relation. The purpose of this study was to assess conditions under which item parameter estimation accuracy increases or decreases, with special…

Proposes a two-stage estimation method for the analysis of covariance structure models with ordinal ipsative data (OID). A goodness-of-fit statistic is given for testing the hypothesized covariance structure matrix, and simulation results show that the method works well with a large sample. (SLD)

A class of two-stage models is developed to accommodate three common characteristics of behavioral data: (1) its multivariate nature; (2) the typical small sample size; and (3) the possibility of missing observations. The model, as illustrated, permits estimation of the full spectrum of plausible measurement error structures. (SLD)

Previous work on the effects of dimensionality on parameter estimation for dichotomous models is extended to the graded response model. Datasets are generated that differ in the number of latent factors as well as their interdimensional association, number of test items, and sample size. (SLD)

Investigated the assumption that determining an adequate sample size in structural equation modeling can be aided by considering the number of parameters to be estimated. Findings from maximum likelihood confirmatory factor analysis support previous research on the effect of sample size, measured variable reliability, and the number of measured…

Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item parameters. Simulated data sets were analyzed using two different Bayes estimation procedures, the two-stage hierarchical Bayes estimation (HB2) and the marginal Bayesian with known hyperparameters (MB), and marginal maximum…

When latent class parameters are estimated, maximum likelihood and Pearson chi-square statistics can be derived for assessing the fit of the model to the data. This study used simulated data to compare these two statistics, and is based on mixtures of latent binomial distributions, using data generated from five dichotomous manifest variables.…

Using Monte Carlo methods, the applicability of large sample theory to maximum likelihood estimates of total indirect effects in sample sizes of 50, 100, 200, 400, and 800 was studied. Samples of at least 200 and 400 are required for the recursive and nonrecursive models, respectively, that were assessed. (TJH)

Studied the small sample behavior of several test statistics based on the maximum-likelihood estimator but designed to perform better with nonnormal data. Monte Carlo results indicate the satisfactory performance of the "F" statistic recently proposed by K. Yuan and P. Bentler (1997). (SLD)

Used simulation to demonstrate how the choice of estimation method affects indexes of fit and parameter bias for different sample sizes when nested models vary in terms of specification error and the data demonstrate different levels of kurtosis. Discusses results for maximum likelihood (ML), generalized least squares (GLS), and weighted least…

Actual kurtotic and skewed data and varied sample sizes and estimation methods demonstrated that normal theory maximum likelihood and generalized least square estimators were fairly consistent and almost identical. Standard errors tended to underestimate the estimator's true variation but the problem was not serious for large samples. (SLD)

A method is proposed for partially analyzing additive ipsative data (PAID). Transforming the PAID according to a developed equation preserves the density of the transformed data, and maximum likelihood estimation can be carried out as usual. Simulation results show that the original structural parameters can be accurately estimated from PAID. (SLD)

Asymptotic distributions of H. Brogden's and F. Lord's modified sample biserial correlation coefficients (SBCCs) are derived. Asymptotic variances of these estimators are evaluated for bivariate normal populations and compared to the maximum likelihood estimator's asymptotic variance. These estimators are less variable than ordinary SBCCs when the…

The accuracy of estimation procedures in item response theory was studied using Monte Carlo methods and varying sample size, number of subjects, and distribution of ability parameters for: (1) joint maximum likelihood as implemented in the computer program LOGIST; (2) marginal maximum likelihood; and (3) marginal Bayesian procedures as implemented…