Package: drord 1.0.1.9000

drord: Doubly-Robust Estimators for Ordinal Outcomes

Efficient covariate-adjusted estimators of quantities that are useful for establishing the effects of treatments on ordinal outcomes (Benkeser, Diaz, Luedtke 2020 <doi:10.1111/biom.13377>)

Authors:David Benkeser [aut, cre, cph]

drord_1.0.1.9000.tar.gz
drord_1.0.1.9000.zip(r-4.7-any)drord_1.0.1.9000.zip(r-4.6-any)drord_1.0.1.9000.zip(r-4.5-any)
drord_1.0.1.9000.tgz(r-4.6-any)drord_1.0.1.9000.tgz(r-4.5-any)
drord_1.0.1.9000.tar.gz(r-4.7-any)drord_1.0.1.9000.tar.gz(r-4.6-any)
drord_1.0.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
drord/json (API)

# Install 'drord' in R:

install.packages('drord', repos = c('https://benkeser.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/benkeser/drord/issues

Datasets:

covid19 - Simulated COVID-19 outcomes for hospitalized patients.

On CRAN:

causal-inference covid-19 double-robust mann-whitney ordinal-regression

4.44 score 5 stars 11 scripts 361 downloads 1 exports 25 dependencies

Last updated from:112d8041c7. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel	NOTE	186
source / vignettes	OK	223
linux-release	NOTE	164
macos-release	NOTE	151
macos-oldrel	NOTE	146
windows-devel	NOTE	131
windows-release	NOTE	126
windows-oldrel	NOTE	128
wasm-release	OK	92

Exports:drord

Dependencies:cli cpp11 farver ggplot2 glue gtable isoband labeling lattice lifecycle MASS Matrix nlme numDeriv ordinal R6 RColorBrewer rlang S7 scales ucminf vctrs VGAM viridisLite withr

drord: Doubly robust estimators of ordinal treatment effects

Rendered fromusing_drord.Rmdusingknitr::rmarkdown

Last update: 2021-05-20
Started: 2020-05-20

Citation

Development and contributors

Readme and manuals

Help Manual

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