|
|
|
|
|
Alexander Robitzsch
Item response theory (IRT) models are frequently used to analyze multivariate categorical data from questionnaires or cognitive test data. In order to reduce the model complexity in item response models, regularized estimation is now widely applied, addi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexander Robitzsch
The local independence assumption is crucial for the consistent estimation of item parameters in item response theory models. This article explores a pairwise likelihood estimation approach for the two-parameter logistic (2PL) model that treats the local...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexander Robitzsch
Missing item responses are frequently found in educational large-scale assessment studies. In this article, the Mislevy-Wu item response model is applied for handling nonignorable missing item responses. This model allows that the missingness of an item ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexander Robitzsch
This article reviews several implementation aspects in estimating regularized single-group and multiple-group structural equation models (SEM). It is demonstrated that approximate estimation approaches that rely on a differentiable approximation of non-d...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexander Robitzsch
Structural equation models (SEM) are widely used in the social sciences. They model the relationships between latent variables in structural models, while defining the latent variables by observed variables in measurement models. Frequently, it is of int...
ver más
|
|
|
|
|
|
|
|
|
|
|
Alexander Robitzsch
The mixture Rasch model is a popular mixture model for analyzing multivariate binary data. The drawback of this model is that the number of estimated parameters substantially increases with an increasing number of latent classes, which, in turn, hinders ...
ver más
|
|
|
|
|
|