mRm-package

This package provides routines for cML estimation and model selection in binary mixed Rasch models (Rost 1990). For a detailed discussion of the accuracy of parameter estimates and reliability of AIC- and BIC- based model selection techniques see Preinerstorfer and Formann (2011). The core part of the algorithm has been implemented in C++, using parts of the Scythe Statistical Library (2007) for matrix manipulations. Rows with missing values and constant rows are excluded.

Conditional maximum likelihood estimation via the EM algorithm and information-criterion-based model selection in binary mixed Rasch models.

David Preinerstorfer

An R Package for Conditional Maximum Likelihood Estimation in
Mixed Rasch Models

mRm-package function

This package provides routines for cML estimation and model selection in binary mixed Rasch models (Rost 1990). For a detailed discussion of the accuracy of parameter estimates and reliability of AIC- and BIC- based model selection techniques see Preinerstorfer and Formann (2011). 

The core part of the algorithm has been implemented in C++, using parts of the Scythe Statistical Library (2007) for matrix manipulations. Rows with missing values and constant rows are excluded.

mRm-package: Parameter estimation and model selection in mixed Rasch models.

Description

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