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.
Models for categorical data: a comparison between the Rasch model and nonlinear principal component analysis.
BRENTARI, Eugenio;GOLIA, Silvia;MANISERA, Marica
2007-01-01
Abstract
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.File in questo prodotto:
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