This article proposes that sampling design effects have potentially huge unrecognized impacts on the results reported by large-scale district and state assessments in the United States. When design effects are unrecognized and unaccounted for they lead to underestimating the sampling error in item and test statistics. Underestimating the sampling…

Articles on equating test forms in this issue are reviewed and discussed. The results of these papers collectively indicate that matching on the anchor test does not result in more accurate equating. Implications for research are discussed. (SLD)

Problems in selection of optimal designs in item-response theory (IRT) models are resolved through a sequential design procedure that is a modification of the D-optimality procedure proposed by Wynn (1970). This algorithm leads to consistent estimates, and the errors in selecting the abilities generally do not greatly affect optimality. (SLD)

Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data…

The equating methods and sampling designs used in the empirical studies in this special issue on the use of matched samples for test equating are described. Four requisites for equating are listed, and the invariance of equating functions requisite is identified as the focus of this issue. (SLD)

A generalized variance criterion is used for sequential sampling in the two-parameter item response theory model. Some principles are offered to enable the researcher to select the best sampling design for efficient estimation of item parameters. Topics include the choice of an optimality criterion, two-stage designs, and sequential designs. (SLD)

A generalized variance criterion is proposed to measure efficiency in item-response-theory (IRT) models. Heuristic arguments are given to formulate the efficiency of a design in terms of an asymptotic generalized variance criterion. Efficiencies of designs for one-, two-, and three-parameter models are compared. (SLD)

A method is suggested to estimate the relationship between a latent trait and one or more manifest predictors without estimating subject parameters. The method, developed for the Rasch model, can be generalized to two-parameter and three-parameter logistic latent trait models. The model is illustrated with simulated and empirical data. (SLD)