This packages provides a function to estimate parameters
for the mixed conditional logit model, or conditional logit
with random effects. The current implementation is limited to
random intercepts and to the PQL technique, mainly appropriate
for large clusters.

This packages provides a function to estimate parameters for the
mixed conditional logit model, or conditional logit with random effects.
The current implementation is limited to random intercepts and to
the PQL technique, mainly appropriate for large clusters.

This packages provides a function to estimate parameters
for the mixed conditional logit model, or conditional logit
with random effects.  The current implementation is limited to
random intercepts and to the PQL technique, mainly appropriate
for large clusters.

This packages provides a function to estimate parameters for the
mixed conditional logit model, or conditional logit with random effects.
The current implementation of random effects is limited to
the PQL technique, which requires large cluster sizes.

This packages provides a function to estimate parameters for
the conditional logit model (also with multinomial counts), and for the
mixed conditional logit model, or conditional logit with random effects
(random intercepts only, no random slopes yet).
The current implementation of random effects is limited to
the PQL technique, which requires large cluster sizes.

Specification and estimation of conditional logit models of binary responses and multinomial counts is provided,
with or without alternative-specific random effects (random intercepts only, no random slopes yet).
The current implementation of the estimator for random effects variances uses a Laplace approximation (or PQL)
approach and thus should be used only if groups sizes are large.

Specification and estimation of conditional logit models of binary
responses and multinomial counts is provided, with or without alternative-
specific random effects. The current implementation of the estimator for random
effects variances uses a Laplace approximation (or PQL) approach and thus should
be used only if groups sizes are large.