Quantile-Optimal Treatment Regimes with Censored Data

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Documentation for package ‘QTOCen’ version 0.1.1

• DESCRIPTION file.

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Bnk_func	Generate biquadratic kernel weights for a univariate variable
est_mean_ipwe	Estimate the marginal mean response of a linear static treatment regime
est_quant_ipwe	Estimate the marginal quantile response of a linear static treatment regime
est_quant_TwoStg_ipwe	Estimate the marginal quantile response of a specific dynamic TR
Gene_Mean_CenIPWE	A low-level function for the generic optimization step in estimating Mean-optimal treatment regime for censored data
Gene_Quantile_CenIPWE	A low-level function for the generic optimization step in estimating Quanilte-optimal treatment regime for censored data
Gene_Quantile_CenIPWE_DTR	A low-level function for the generic optimization step in estimating dynamic Quanilte-optimal treatment regime for censored data
IPWE_mean_IndCen	Estimate the mean-optimal treatment regime for data with independently censored response
IPWE_Qopt_DepCen_general	Estimate Quantile-optimal Treatment Regime for covariates-dependent random censoring data
IPWE_Qopt_DepCen_trt	Estimate the Quantile-opt Treatment Regime under the assumption that the censoring time's distribution only depends on treatment level
IPWE_Qopt_DTR_IndCen	Function to estimate the two-stage quantile-optimal dynamic treatment regime for censored data: the independent censoring Case
IPWE_Qopt_IndCen	Function to estimate the quantile-optimal treatment regime: the independent censoring Case
LocalKM	Kernel-based Local Kaplan-Meier Estimator
simJLSDdata	Function to generate simulation data from a sequentially randomized experiment designed in (Jiang et al. 2017)
tauhat_func	Kernel-based Local Kaplan-Meier Estimator for the Conditional Probability of the Survival Time