jshinb/pmlr:
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 first-order 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, score or Wald statistics. Profile confidence intervals (CI) are constructed for the PLEs.
Getting started
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Package details |
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| Author | Sarah Colby <colby@lunenfeld.ca>, Sophia Lee, Juan Pablo Lewinger, Shelley Bull <bull@lunenfeld.ca>, Michael Rotondi <mrotondi@yorku.ca>, Ji-Hyung Shin <shin.jihyung@gmail.com> |
| Maintainer | Sarah Colby <mrotondi@yorku.ca> |
| License | GPL (>= 2) |
| Version | 1.1.1 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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