get_TMLE_RDs

A list of objects returned by <code><a rd-options="" href="/link/fitIterTMLE?package=stremr&version=0.4" data-mini-rdoc="stremr::fitIterTMLE">fitIterTMLE</a></code>, <code><a rd-options="" href="/link/fitTMLE?package=stremr&version=0.4" data-mini-rdoc="stremr::fitTMLE">fitTMLE</a></code> or <code><a rd-options="" href="/link/fitSeqGcomp?package=stremr&version=0.4" data-mini-rdoc="stremr::fitSeqGcomp">fitSeqGcomp</a></code>.

TMLE_list

Vector of time-points for evaluation of pairwise risk differences.

t.periods.RDs


Produces table(s) with pair-wise risk differences for all regimens that were used for fitting TMLE.
The corresponding SEs are evaluated based on the estimated influence curves (IC).


Analysis of longitudinal time-to-event or time-to-failure data.
Estimates the counterfactual discrete survival curve under static, dynamic and
stochastic interventions on treatment (exposure) and monitoring events over time.
Estimators (IPW, MSM-IPW, GCOMP, longitudinal TMLE) adjust for measured time-varying
confounding and informative right-censoring. Model fitting can be performed either
with GLM or H2O-3 machine learning libraries.
The exposure, monitoring and censoring variables can be coded as either binary,
categorical or continuous. Each can be multivariate (e.g., can use more than one
column of dummy indicators for different censoring events).
The input data needs to be in long format.

Oleg Sofrygin

stremr

Streamlined Estimation of Survival for Static, Dynamic and
Stochastic Treatment and Monitoring Regimes

get_TMLE_RDs function

A list of objects returned by <code><a rd-options='' href='fitIterTMLE'>fitIterTMLE</a></code>, <code><a rd-options='' href='fitTMLE'>fitTMLE</a></code> or <code><a rd-options='' href='fitSeqGcomp'>fitSeqGcomp</a></code>.

get_TMLE_RDs: Risk Difference Estimates and SEs for a list of TMLE outputs

Description

Usage

Arguments

Value

See Also