Multinomial Logit Models for Categorical Responses and Discrete Choices
Overdispersion in Multinomial Logit Models
getSummary Methods
Baseline-Category Logit Models for Categorical and Multinomial Respons...
Control Parameters for the Fitting Process
Internal functions used for model fit.
Conditional Logit Models and Mixed Conditional Logit Models
Predicting responses or linear parts of the baseline-category and cond...
Change baseline category of multinomial logit or similar model
Simulating responses from baseline-category and conditional logit mode...
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.
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