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)

Examined the relative performance of two commonly used methods of parameter estimation in factor analysis, maximum likelihood (ML) and ordinary least squares (OLS) through simulation. In situations with a moderate amount of error, ML often failed to recover the weak factor while OLS succeeded. Also presented an example using empirical data. (SLD)

A simulation study explored the effect of population distribution on maximum likelihood estimation (MLE) and expected a posteriori (EAP) estimation in computerized adaptive testing based on the rating scale model of D. Andrich (1978). The choice between EAP and MLE for particular situations is discussed. (SLD)

Loglinear latent class models are used to detect differential item functioning (DIF). Likelihood ratio tests for assessing the presence of various types of DIF are described, and these methods are illustrated through the analysis of a "real world" data set. (TJH)

Standard procedures for estimating item parameters in item response theory ignore collateral information that may be available about examinees. Circumstances under which collateral information about examinees may be used to make inferences about item parameters more precise and circumstances under which collateral information must be used are…

A model is proposed for investigating test validity as a predictor of a criterion variable when there are both missing and censored scores in the data set. Implications for maximum likelihood estimation are discussed, and the method is illustrated with hypothetical data sets. (SLD)

A model for student retention and attrition is presented. Focus is on alternative models for the "dampening" in attrition rates as educational programs progress. Maximum likelihood estimates for the underlying parameters in each model and a Bayesian analysis are provided. (TJH)

Path Analysis of Covariance Matrix (PACM) is described as a way to separately estimate measurement and structural models using standard least squares procedures. PACM was empirically compared to simultaneous maximum likelihood estimation and use of the LISREL computer program, and its advantages are identified. (SLD)

A stochastic version of a knowledge space is developed in which knowledge states are considered as possible epochs in a subject's learning history. It specifies how a subject is channeled through and progresses along a "gradation." The model's application to artificial data is described, based on maximum likelihood methods. (TJH)

Confirmatory maximum likelihood factor analysis determined how accurately each of several hypothesized combinations of first-order and higher-order factors reflecting creativity in the social intelligence of 192 high school students described the covariation in selected submatrixes from the total correlation matrix originally analyzed. Results…

A Monte Carlo study was conducted to investigate the robustness of the assumed error distribution in maximum likelihood estimation models for multidimensional scaling. Results show that violations of the assumed error distribution have virtually no effect on the estimated distance parameters. (SLD)

A maximum likelihood approach to correlational outlier identification is introduced and compared to the Mahalanobis D squared and Comrey D statistics through Monte Carlo simulation. Identification performance depends on the nature of correlational outliers and the measure used, but the maximum likelihood approach is the most robust performance…

Asymptotic distributions of the estimators of communalities are derived for the maximum likelihood method in factor analysis. It is shown that equating the asymptotic standard error of the communality estimate to the unique variance estimate is not correct for the unstandardized case. Monte Carlo simulations illustrate the study. (SLD)

F. Samejima's approximation for the bias function for the maximum likelihood estimate of the latent trait in the general case where item responses are discrete is explored. Observations are made about the behavior of this bias function for the dichotomous response level in general. Empirical examples are given. (SLD)

Simulation studies (N=4,000 simulees) examined the effect of misspecification of the latent ability distribution (theta) on the accuracy and efficiency of marginal maximum likelihood (MML) item parameter estimates and on MML statistics to test sufficiency and conditional independence. Results were compared to those of the conditional maximum…