This paper presents the Latent Class Level-PCM as a method for identifying and interpreting latent classes of respondents according to empirically estimated performance levels. The model, which combines elements from latent class models and reparameterized partial credit models for polytomous data, can simultaneously (a) identify empirical…

This study investigated the relationship between students' actual performance (accuracy) and their subjective judgments of accuracy (confidence) on selected English language proficiency tests. The unidimensional and multidimensional IRT Rasch approaches were used to model the discrepancy between confidence and accuracy at the item and test level…

This paper is the first of several papers designed to demonstrate how the application of item response models in the behavioral sciences can be used to enhance the conceptual and technical toolkit of researchers and developers and to understand better the psychometric properties of psychosocial measures. The papers all use baseline data from the…

Marginal maximum likelihood estimation equations are derived for the structural parameters of the Saltus model, and a computing approximation is suggested based on the EM algorithm. The solution is illustrated with simulated data and an example from the domain of mixed number subtraction. (SLD)

Standard item response theory (IRT) models posit latent variables to account for regularities in students' performance on test items. They can accommodate learning only if the expected changes in performance are smooth, and, in an appropriate metric, uniform over items. Wilson's "Saltus" model extends the ideas of IRT to development that…

A parallel design, in which items across different scales within an instrument share common stimuli and subjects respond to the common stimulus for each scale, is sometimes used in questionnaires or inventories. Because the items across scales share the same stimuli, the assumption of local item independence may not hold, thereby violating the…