fit_trt_spec_reg {drord} | R Documentation |
polr
is used from the MASS
package. Otherwise logistic regression is used. In both cases,
inverse probability of treatment weights are included in the regression.
If there are levels of the outcome that are not observed in this treatment
group, then 0's are added in. The function returns a matrix with named columns
corresponding to each outcome (ordered numerically). The entries
represent the estimated covariate-conditional treatment-specific PMF.Helper function to fit a treatment specific outcome regression.
If there are more than 2 observed levels of the outcome for the
specified treatment arm, then polr
is used from the MASS
package. Otherwise logistic regression is used. In both cases,
inverse probability of treatment weights are included in the regression.
If there are levels of the outcome that are not observed in this treatment
group, then 0's are added in. The function returns a matrix with named columns
corresponding to each outcome (ordered numerically). The entries
represent the estimated covariate-conditional treatment-specific PMF.
fit_trt_spec_reg(
trt_level,
trt_spec_prob_est,
out,
treat,
covar,
out_levels,
out_form = NULL,
out_model,
stratify,
...
)
trt_level |
Which level of treatment to fit the proportional odds model for |
trt_spec_prob_est |
A vector of estimates of Pr( |
out |
A |
treat |
A |
covar |
A |
out_levels |
A |
out_form |
The right-hand side of a regression formula for the working proportional odds model. NOTE: THIS FORMULA MUST NOT SUPPRESS THE INTERCEPT. |
out_model |
Which R function should be used to fit the proportional odds
model. Options are |
stratify |
Boolean indicating whether to use nonparametric maximum likelihood
(i.e., a stratified estimator). If |
... |
Other options (not used). |