Multinomial Logit Models, with or without Random Effects or Overdispersion
Overdispersion in Multinomial Logit Models
getSummary Methods
Baseline-Category Logit Models for Categorical and Multinomial Respons...
Internal functions used for model fit.
Conditional Logit Models and Mixed Conditional Logit Models
Control Parameters for the Fitting Process
Predicting responses or linear parts of the baseline-category and cond...
Simulating responses from baseline-category and conditional logit mode...
Provides estimators for multinomial logit models in their conditional logit and baseline logit variants, with or without random effects, with or without overdispersion. 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.
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