Extends the approach proposed by Firth (1993) for bias reduction of MLEs in exponential family models to the multinomial logistic regression model with general covariate types. Modification of the logistic regression score function to remove firstorder bias is equivalent to penalizing the likelihood by the Jeffreys prior, and yields penalized maximum likelihood estimates (PLEs) that always exist. Hypothesis testing is conducted via likelihood ratio statistics. Profile confidence intervals (CI) are constructed for the PLEs.
Package details 


Author  Sarah Colby <colby@lunenfeld.ca>, Sophia Lee, Juan Pablo Lewinger, Shelley Bull <bull@lunenfeld.ca> 
Date of publication  20100402 17:08:39 
Maintainer  Sarah Colby <colby@lunenfeld.ca> 
License  GPL (>= 2) 
Version  1.0 
Package repository  View on CRAN 
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