As befits a model-fitting function, the package defines a nearly
complete set of methods for class nestedLogit objects:
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print(),summary(): prints the results for each of the submodels -
update()re-fits a model, allowing changes in the modelformula,data,subset, andcontrasts. -
coef()returns the coefficients for the predictors in each dichotomy -
vcov()returns the variance-covariance matrix of the predictors -
predict()obtains predicted probabilities for the response categories, useful for producing plots to aid interpretation. -
glance(),tidy()are extensions ofbroom::glance.glm()andbroom::tidy.glm()to obtain compact summaries of anestedLogitmodel object`. -
plot()provides basic plots of the predicted probabilities over a range of values of the predictor variables. -
models()is an extractor function to extract the separate models binary logit models from the"nestedLogit"object
These are supplemented by various methods for testing hypotheses about nested logit models:
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anova()provides ANOVA Type I (sequential) tests for each dichotomy and for the combined model. When given a sequence of objects,anova()tests the models against one another in the order specified. -
Anova()usescar::Anova()to provide ANOVA Type II (partial) tests for each dichotomy and for the combined model. -
linearHypothesis()gives Wald tests for hypotheses about coefficients or their linear combinations -
logLike()returns the log-likelihood and degrees of freedom for the nested-dichotomies model; - through the last,
AIC()andBIC()provide model-comparison statistics.
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