Models for categorical data: a comparison between the Rasch model and Nonlinear Principal Component Analysis

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Models for categorical data: a comparison between the Rasch model and Nonlinear Principal Component Analysis

Article

Magazine

STATISTICA & APPLICAZIONI

Section

Open Access

Title

Models for categorical data: a comparison between the Rasch model and Nonlinear Principal Component Analysis

Authors

Eugenio Brentari, Silvia Golia, Marica Manisera

Publisher

Vita e Pensiero

Format

Article |

Pdf

Online from

01-2007

Issn

1824-6672 (print) | 2283-6659 (digital)

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Description Readers' comments

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.

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