How item bias indexes based on item response theory (IRT) identify bias that results from multidimensionality is demonstrated. Simulation results suggest that IRT-based bias indexes detect multidimensional items with bias but do not detect multidimensional items without bias. They also do not confound between-group differences on the primary test.…

The equating of results from the PC-BILOG computer program to an underlying metric was studied through simulation when a two-parameter item response theory model was used. Results are discussed in terms of the identification problem and implications for test equating. (SLD)

It is demonstrated, theoretically and empirically, that item sets can be selected that meet the unidimensionality assumption of most item response theory models, even though they require more than one ability for a correct response. A method for identifying such item sets for test development purposes is presented. (SLD)

The capability of the DIMTEST statistical test to assess essential dimensionality of the model underlying item responses of real tests as opposed to simulated tests was investigated. A variety of real test data from difference sources was used to assess essential dimensionality. Based on DIMTEST results, some test data are assessed as fitting an…

Concern has been expressed over the item response theory (IRT) assumption that a person's ability can be estimated in a unidimensional latent space. To examine whether or not the response to an item requires only a single latent ability, unidimensional ability estimates were compared for data generated from the multidimensional item response…

This paper develops and applies three nonparametric comparisons of the shapes of two item characteristic surfaces: (1) proportional latent odds; (2) uniform relative difficulty; and (3) item sensitivity. A method is presented for comparing the relative shapes of two item characteristic curves in two examinee populations who were administered an…

A probabilistic parallelogram model (the PARELLA model) is presented for the measurement of latent traits by proximity items. This unidimensional model assumes that the responses of persons to items result from proximity relations. The model is illustrated in an analysis of three empirical datasets from previous studies. (SLD)

A Monte Carlo study, which simulated 10,000 examinees' responses to four tests, investigated the effect of item stratification on parameter estimation in multiple matrix sampling of achievement data. Practical multiple matrix sampling is based on item stratification by item discrimination and a sampling plan with moderate number of subtests. (SLD)

A didactic example is provided, using a Monte Carlo method, of how differential item functioning (DIF) can be eliminated (and thus better understood) when the complete latent space is used. The main source of DIF is that the matching single criterion used in some DIF procedures, Mantel Haenszel or Simultaneous Item Bias (SIBTEST), does not account…

The phenomenon of simultaneous differential item functioning (DIF) amplification and cancellation and the role of the SIBTEST approach in detecting DIF are investigated with a variety of simulated test data. The effectiveness of SIBTEST is supported, and the implications of DIF amplification and cancellation are discussed. (SLD)

The effectiveness of two iterative methods of item response theory (IRT) item bias detection was examined in a simulation study. A modified form of the iterative item parameter linking method of F. Drasgow and an adaptation of the test purification procedure of F. M. Lord were compared. (SLD)

This study reports results of an investigation based on simulated data of the distributional properties of the item fit statistics that are commonly used in the Rasch model calibration programs as indices of the fit of responses to individual items to the measurement model. (SLD)

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…

The sensitivity of marginal maximum likelihood estimation of item and ability (theta) parameters was examined when prior ability distributions were not matched to underlying ability distributions. Thirty sets of 45-item test data were generated. Conditions affecting the accuracy of estimation are discussed. (SLD)

The PARallELogram Analysis (PARELLA) model is a probabilistic parallelogram model that can be used for the measurement of latent attitudes or latent preferences. A method is presented for testing for differential item functioning (DIF) for the PARELLA model using the approach of D. Thissen and others (1988). (SLD)