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 des...
This paper describes the R package cold for the analysis of count longitudinal data. In this package...
In longitudinal studies measurements are often collected on different types of outcomes for each sub...
The R package lcmm provides a series of functions to estimate statistical models based on linear mix...
In recent years, targeted minimum loss-based estimation methodology has been used to develop estimat...
Sequential Randomized Controlled Trials (SRCTs) are rapidly becoming essential tools in the search f...
Targeted maximum likelihood estimation (TMLE) is a general approach for constructing an efficient do...
This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudin...
R code disponible : https://www.mireilleschnitzer.com/collaborative-longitudinal-tmle.htmlCausal inf...
Targeted minimum loss based estimation (TMLE) provides a template for the construction of semiparame...
In many randomized controlled trials the outcome of interest is a time to event, and one measures on...
Longitudinal targeted maximum likelihood estimation (LTMLE) has very rarely been used to estimate dy...
Longitudinal targeted maximum likelihood estimation (LTMLE) has hardly ever been used to estimate dy...
Applying targeted maximum likelihood estimation to longitudinal data can be computationally intensiv...
This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudin...
In longitudinal studies measurements are often collected on different types of outcomes for each sub...
This paper describes the R package cold for the analysis of count longitudinal data. In this package...
In longitudinal studies measurements are often collected on different types of outcomes for each sub...
The R package lcmm provides a series of functions to estimate statistical models based on linear mix...
In recent years, targeted minimum loss-based estimation methodology has been used to develop estimat...
Sequential Randomized Controlled Trials (SRCTs) are rapidly becoming essential tools in the search f...
Targeted maximum likelihood estimation (TMLE) is a general approach for constructing an efficient do...
This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudin...
R code disponible : https://www.mireilleschnitzer.com/collaborative-longitudinal-tmle.htmlCausal inf...
Targeted minimum loss based estimation (TMLE) provides a template for the construction of semiparame...
In many randomized controlled trials the outcome of interest is a time to event, and one measures on...
Longitudinal targeted maximum likelihood estimation (LTMLE) has very rarely been used to estimate dy...
Longitudinal targeted maximum likelihood estimation (LTMLE) has hardly ever been used to estimate dy...
Applying targeted maximum likelihood estimation to longitudinal data can be computationally intensiv...
This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudin...
In longitudinal studies measurements are often collected on different types of outcomes for each sub...
This paper describes the R package cold for the analysis of count longitudinal data. In this package...
In longitudinal studies measurements are often collected on different types of outcomes for each sub...
The R package lcmm provides a series of functions to estimate statistical models based on linear mix...