validate_censor_formula

Checks that the censoring formula is valid, uses Surv() notation, and
extracts the time and event variable names.

internal

Implements propensity score weighting methods for estimating
counterfactual survival functions, marginal hazard ratios, and
weighted Kaplan-Meier and cumulative risk curves in observational
studies with time-to-event outcomes. Supports binary and multiple
treatment groups with inverse probability of treatment weighting (IPW),
overlap weighting (OW), and average treatment effect on the treated
(ATT). Includes symmetric trimming (Crump extension) for extreme
propensity scores. Variance estimation via analytical M-estimation or
bootstrap. Methods based on Li et al. (2018) <doi:10.1080/01621459.2016.1260466>,
Li & Li (2019) <doi:10.1214/19-AOAS1282>, and Cheng et al. (2022)
<doi:10.1093/aje/kwac043>.

Chengxin Yang

PSsurvival

Propensity Score Methods for Survival Analysis

Chao Cheng

Fan Li

validate_censor_formula function

<dl><dt>censor_formula</dt>
<dd>A formula object for the censoring model.
Should be of the form `Surv(time, event) ~ covariates`.
Use `Surv(time, event) ~ 0` to indicate no censoring adjustment
(all censoring scores set to 1).</dd></dl>

Arguments

Validate Censoring Formula — validate_censor_formula

<dl>

<dt>censor_formula</dt>
<dd>A formula object for the censoring model.
Should be of the form `Surv(time, event) ~ covariates`.
Use `Surv(time, event) ~ 0` to indicate no censoring adjustment
(all censoring scores set to 1).</dd>

</dl>

validate_censor_formula: Validate Censoring Formula

Description

Usage

Value

Arguments