It is shown how two extensions of the latent Markov model that have been developed by Rolf Langeheine and his colleagues (latent mixed Markov models, latent state-trait models) can be integrated into a common general frame of reference. In particular, it is demonstrated that latent state-trait models are a special subgroup of latent mixed Markov models. The different chains of a latent mixed Ma...

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspon...

This paper examined various factors affecting linking accuracy of the augmented tests containing both common assessments and state-specific item sets in the context of the Common Core State Standards (CCSS). Linking was conducted using the common-item nonequivalent groups design with pseudo and simulated data. The factors included group ability differences, differential effect sizes, latent-tra...

aim and background: the aim of the present study was to investigatethe psychometric properties of the trait hope scale and its relation with psychological well-being of iranian university students. methods and materials: in this descriptivesurvey, 191 students of hamadan islamic azad university (mean age: 24.17 ± 4.30 years; range: 18-45 years) were selected through stratified randomsampling.th...

A model is presented which allows for the contribution of genes and environment to categorical data on multiple symptoms. The model distinguishes between parameters needed to express the relationship between a latent trait and observed responses and the parameters required to represent the causes of variation in the latent trait. The regression of the latent trait on covariates may also be spec...

The issue of latent trait granularity in diagnostic models is considered, comparing and contrasting latent trait and latent class models used for diagnosis. Relationships between conjunctive cognitive diagnosis models (CDMs) with binary attributes and noncompensatory multidimensional item response models are explored, leading to a continuous generalization of the Noisy Input, Deterministic ‘‘An...