Developed two methods for estimating the individual level correlation coefficient that combines information from aggregate data with a small fraction of the individual level data. Results of a simulation study support the use of these methods. (SLD)

Three alternative estimation procedures for factor analysis based on the instrumental variables method are presented. Least squares estimation procedures are compared to maximum likelihood procedures. The conclusion, based on the data used in this study, is that two of the procedures seem to work well. (Author/JKS)

Nonlinear common factor models with polynomial regression functions, including interaction terms, are fitted by simultaneously estimating the factor loadings and common factor scores, using maximum likelihood and least squares methods. A Monte Carlo study gives support to a conjecture about the form of the distribution of the likelihood ratio…

This study examines the application of the marginal maximum likelihood (MML) EM algorithm to the parameter estimation problem of the three-parameter normal ogive and logistic polychotomous item response models. A three-parameter normal ogive model, the Graded Response model, has been developed on the basis of Samejima's two-parameter graded…

The purpose of this study was to compare and evaluate three online pretest item calibration/scaling methods in terms of item parameter recovery when the item responses to the pretest items in the pool would be sparse. The three methods considered were the marginal maximum likelihood estimate with one EM cycle (OEM) method, the marginal maximum…