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ltmle: An R Package Implementing Targeted Minimum Loss-Based Estimation for Longitudinal Data

delete2017-01-01
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S
Samuel Lendle *
P
Petersen, Maya L.
S
Schwab, Joshua
M
Mark J. van der Laan
DOI:10.18637/jss.v081.i01delete
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摘要

摘要

En 中文
In recent years, targeted minimum loss-based estimation methodology has been used to develop estimators of parameters in longitudinal data structures (Gruber and van der Laan 2012; Petersen, Schwab, Gruber, Blaser, Schomaker, and van der Laan 2014; Schnitzer, Moodie, van der Laan, Platt, and Klein 2013). These methods are implemented in the ltmle package for R. The ltmle package provides methods to estimate intervention-specific means and measures of association including the average treatment effect, causal odds ratio and causal risk ratio and parameters of a longitudinal working marginal structural model. The package allows for multiple time point treatments, time-varying covariates and right censoring of the outcome. In this paper we described the usage of the ltmle package and provide examples.
Keyword:
targeted minimum loss-based estimation
longitudinal data
causal inference
estimation
R

期刊

Journal of Statistical Software 封面图
Journal of Statistical Software
IF:
8.1
论文数:
622
被引数:
4.6W

机构

University of California System 封面图
University of California System
学者数:
37.7W
论文数: 33.8W
被引数: 6.6K
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