fit_survival_models

Various methods for targeted and semiparametric inference including
augmented inverse probability weighted (AIPW) estimators for missing data and
causal inference (Bang and Robins (2005) <doi:10.1111/j.1541-0420.2005.00377.x>),
one-step imputation (Nordland et al (2026)) <doi:10.48550/arXiv.2606.07174>),
variable importance and conditional average treatment effects (CATE)
(van der Laan (2006) <doi:10.2202/1557-4679.1008>),
estimators for risk differences and relative risks (Richardson et al. (2017)
<doi:10.1080/01621459.2016.1192546>), assumption lean inference for generalized
linear model parameters (Vansteelandt et al. (2022) <doi:10.1111/rssb.12504>).

Klaus Holst

targeted

Targeted Inference

Klaus K. Holst

Benedikt Sommer

Andreas Nordland

Christian B. Pipper

fit_survival_models function

<dl><dt>data</dt>
<dd>data.frame</dd>
<dt>response</dt>
<dd>Response formula (e.g., Surv(time, event) ~ A + W)</dd>
<dt>censoring</dt>
<dd>Censoring formula (e.g., Surv(time, event == 0) ~ A + W))</dd>
<dt>response_call</dt>
<dd>Model call for the response model (e.g. "mets::phreg")</dd>
<dt>response_args</dt>
<dd>Additional arguments passed to the response model</dd>
<dt>censoring_call</dt>
<dd>Similar to response_callb</dd>
<dt>censoring_args</dt>
<dd>Similar to response_args</dd></dl>

Arguments

Author

Fit survival nuisance models — fit_survival_models

<dl>

<dt>data</dt>
<dd>data.frame</dd>


<dt>response</dt>
<dd>Response formula (e.g., Surv(time, event) ~ A + W)</dd>


<dt>censoring</dt>
<dd>Censoring formula (e.g., Surv(time, event == 0) ~ A + W))</dd>


<dt>response_call</dt>
<dd>Model call for the response model (e.g. "mets::phreg")</dd>


<dt>response_args</dt>
<dd>Additional arguments passed to the response model</dd>


<dt>censoring_call</dt>
<dd>Similar to response_callb</dd>


<dt>censoring_args</dt>
<dd>Similar to response_args</dd>

</dl>

Fit survival nuisance models

fit_survival_models: Fit survival nuisance models

Description

Usage

Value

Arguments

Author