Doubly-Robust Estimators for Ordinal Outcomes

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Documentation for package ‘drord’ version 1.0.1

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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