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mclogit: Multinomial Logit Models for Categorical Responses and Discrete Choices
Provides estimators for multinomial logit models in their conditional logit (for discrete choices) and baseline logit variants (for categorical responses), optionally with overdispersion or random effects. Random effects models are estimated using the PQL technique (based on a Laplace approximation) or the MQL technique (based on a Solomon-Cox approximation). Estimates should be treated with caution if the group sizes are small.
Getting started
Approximate Inference for Multinomial Logit Models with Random Effects
Baseline-category logit models
Conditional logit models
Random effects in baseline logit models and conditional logit models
The IWLS algorithm used to fit conditional logit models
The relation between baseline logit and conditional logit models
Browse package contents
Package details |
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| Author | Martin Elff [aut, cre] |
| Maintainer | Martin Elff <martin@elff.eu> |
| License | GPL-2 |
| Version | 0.9.15 |
| URL | http://melff.github.io/mclogit/ https://github.com/melff/mclogit/ |
| Package repository | View on CRAN |
| Installation |
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