twopartm-class | R Documentation |
twopartm
A fitted two-part regression model by tpm
.
formula_part1
Formula specified for the first-part model, i.e., the binomial model for indicators about any non-zero responses.
formula_part2
Formula specified for the second-part model, i.e., the glm model for non-zero responses.
data
Data set used to fit the two-part model. It's the same data set as the data
argument in tpm.
n
:Number of observations used in the two-part model (with weights > 0).
n_part1
Number of of observations used in the first-part model (with weights > 0), i.e., the binomial model for indicators about any non-zero responses.
n_part2
Number of of observations used in the second-part model (with weights > 0), i.e., the glm model for non-zero responses.
data_model1
The model frame for the first-part model, i.e., the binomial model for indicators about any non-zero responses.
data_model2
The model frame for the second-part model, i.e., the glm model for non-zero responses.
model_part1
An object of class glm
of the fitted first-part model, i.e., the binomial model for indicators about any non-zero responses.
model_part2
An object of class glm
of the fitted second-part model, i.e., the glm model for non-zero responses.
link_part1
Character string describing the link function of the first-part model, i.e., the binomial model for indicators about any non-zero responses.
family_part2
The family object used in the second-part model, i.e., the glm model for non-zero responses.
weights
A vector of weights used in the two-part model fitting, or NULL if no weights used.
fitted
Fitted mean values by the two-part model, obtained by multiplying the fitted probabilities of non-zero responses and the fitted means of non-zero responses.
residuals
A vector of raw residuals (observed - fitted).
loglik
Log-likelihood values of the fitted two-part model.
y
The response vector.
Yajie Duan, Birol Emir, Griffith Bell and Javier Cabrera
tpm
, AME
, margin
, glm
##data about health expenditures, i.e., non-negative continuous response data(meps,package = "twopartm") ##fit two-part model with the same regressors in both parts, with logistic regression model ##for the first part, and glm with Gamma family with log link for the second-part model tpmodel = tpm(formula_part1 = exp_tot~female+age, formula_part2 = exp_tot~female+age+ed_colplus, data = meps,link_part1 = "logit",family_part2 = Gamma(link = "log")) ##get the formula specified for the first-part model tpmodel@formula_part1 ##get the formula specified for the second-part model tpmodel@formula_part2 ##get the log-likelihood for the fitted two-part model tpmodel@loglik ##get the fitted glm model for the first part tpmodel@model_part1 ##get the fitted glm model for the second part tpmodel@model_part2
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