R: Conditional Probit Model for Analysing Continuous Outcomes

# Conditional Probit Model for Analysing Continuous Outcomes

## Documentation for package ‘cprobit’ version 1.0.2

- DESCRIPTION file

## Help Pages

bg_variability | Inpatient blood glucose data for 1200 patients
compile_est | Inpernal function: generate commonly used summary statistics for estimates.
cprobit | Apply the three-step workflow for the analysis of two repeated outcomes from each subject
cprobit_step1 | Inpernal function: step 1 of the proposed workflow
estimate_sd_error | Inpernal function: estimate the SD of error terms in the difference model
geom_mean | Inpernal function: compute geometric mean of a positive variable
get_v | Inpernal function: compute difference in the (transformed) outcome
make_design_mat | Inpernal function: construct design matrix without the intercept term.
print.cprobit | Apply the three-step workflow for the analysis of two repeated outcomes from each subject
profile_llh | Inpernal function: profile log-likelihood of lambda
summary.cprobit | Apply the three-step workflow for the analysis of two repeated outcomes from each subject
update_estimate | Inpernal function: update Step 1 estimates to obtain linear exposure effect on (transformed) outcome