Models for categorical data: a comparison between the Rasch model and Nonlinear Principal Component Analysis
| STATISTICA & APPLICAZIONI - 2007 - 1
The paper compares two models to construct measures from the responses on a set of categorical
variables, the Rasch Model and the Nonlinear (Categorical) Principal Component Analysis, and
can be considered as a part of the literature about the choice between stochastic and algorithmic
models. The aim is to discuss the Rasch Model and Nonlinear PCA differences and similarities, emphasizing
the information that can be drawn from the data, and to compare the resulting measures.