R: Doubly-Robust Estimators for Ordinal Outcomes

# Doubly-Robust Estimators for Ordinal Outcomes

## Documentation for package ‘drord’ version 1.0.1

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

bca_interval | Compute a BCa confidence interval
bca_logodds | Compute a BCa bootstrap confidence interval for the weighted mean. The code is based on the slides found here: http://users.stat.umn.edu/~helwig/notes/bootci-Notes.pdf
bca_mannwhitney | Compute a BCa bootstrap confidence interval for the Mann-Whitney parameter. The code is based on the slides found here: http://users.stat.umn.edu/~helwig/notes/bootci-Notes.pdf
bca_marg_dist | Compute a BCa bootstrap confidence interval for the weighted mean. The code is based on the slides found here: http://users.stat.umn.edu/~helwig/notes/bootci-Notes.pdf
bca_wmean | Compute a BCa bootstrap confidence interval for the weighted mean. The code is based on the slides found here: http://users.stat.umn.edu/~helwig/notes/bootci-Notes.pdf
compute_trt_spec_bca_intervals | Used to compute treatment-specific BCa intervals for the CDF and PMF
compute_trt_spec_marg_dist_ptwise_ci | Compute simultaneous confidence interval for treatment-specific marginal distribution
compute_trt_spec_marg_dist_simul_ci | Compute simultaneous confidence interval for treatment-specific marginal distribution
covid19 | Simulated COVID-19 outcomes for hospitalized patients.
drord | Doubly robust estimates of for evaluating effects of treatments on ordinal outcomes.
eif_pmf_k | Get EIF estimates for treatment-specific PMF at a particular level of the outcome
eif_theta_k | Get EIF estimates for treatment-specific CDF at a particular level of the outcome
estimate_cdf | Map an estimate of the conditional PMF into an estimate of the conditional CDF
estimate_ci_logodds | Compute confidence interval/s for the log-odds parameters
estimate_ci_mannwhitney | Compute confidence interval/s for the Mann-Whitney parameter
estimate_ci_marg_dist | Compute confidence interval/s for the treatment specific PMF and CDF.
estimate_ci_wmean | Compute confidence interval/s for the weight mean parameters
estimate_cond_mean | Map an estimate of treatment-specific PMF into an estimate of treatment specific conditional mean for each observation.
estimate_eif_wmean | Obtain an estimate of the efficient influence function for the treatment-specific weighted mean parameter
estimate_logodds | implements a plug-in estimator of equation (2) in Diaz et al
estimate_mannwhitney | Compute the estimate of Mann-Whitney based on conditional CDF and PMF
estimate_pmf | Get a treatment-specific estimate of the conditional PMF. Essentially this is a wrapper function for 'fit_trt_spec_reg', which fits the proportion odds model in a given treatment arm.
estimate_treat_prob | Estimate probability of receiving each level of treatment
estimate_wmean | Compute the estimate of the weighted mean parameter based on estimated PMF in each treatment arm.
evaluate_beta_cov | Get the covariance matrix for beta
evaluate_mannwhitney_gradient | Compute the estimated gradient of the Mann-Whitney parameter. Needed to derive standard error for Wald confidence intervals.
evaluate_marg_cdf_eif | Get eif estimates for treatment-specific CDF
evaluate_marg_cdf_ptwise_ci | Evaluate pointwise confidence interval for marginal CDF.
evaluate_marg_dist_simul_ci | Evaluate simultaneous confidence interval for marginal PMF or CDF.
evaluate_marg_pmf_eif | Get eif estimates for treatment-specific PMF
evaluate_marg_pmf_ptwise_ci | Evaluate pointwise confidence interval for marginal PMF.
evaluate_theta_cov | get a covariance matrix for the estimated CDF
evaluate_trt_spec_pmf_eif | Get a matrix of eif estimates for treatment-specific PMF
evaluate_trt_spec_theta_eif | get a matrix of eif estimates for the treatment-specific CDF estimates
fit_trt_spec_reg | 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.
getResponseFromFormula | Get a response from model formula
get_one_logodds | Compute one log odds based on a given data set.
get_one_mannwhitney | Compute one estimate of Mann-Whitney parameter based on a given data set.
get_one_marg_dist | Compute one estimate of the marginal CDF/PMF on a given data set.
get_one_wmean | Compute one weighted mean based on a given data set.
jack_logodds | Compute jackknife log-odds estimates.
jack_mannwhitney | Compute Mann-Whitney log-odds estimates.
jack_marg_cdf | Compute jackknife distribution estimates.
jack_wmean | Compute jackknife weighted mean estimates.
marginalize_cdf | Marginalize over empirical distribution to obtain marginal treatment-specific CDF estimate.
marginalize_pmf | Marginalize over empirical distribution to obtain marginal treatment-specific PMF estimate.
one_boot_logodds | Get one bootstrap computation of the log odds parameters.
one_boot_mannwhitney | Get one bootstrap computation of the Mann-Whitney parameter.
one_boot_marg_dist | Get one bootstrap computation of the CDF and PMF estimates
one_boot_wmean | Get one bootstrap computation of the weighted mean parameters.
plot.drord | Print the output of a '"drord"' object.
POplugin | Fits a proportional odds model via pooled logistic regression.
predict.POplugin | Predict method for a 'POplugin' object
print.drord | Print the output of a '"drord"' object.
trimmed_logit | Trimmed logistic function
wald_ci_wmean | Compute a Wald confidence interval for the weighted mean