Search Results - subject:"G-computation"

Longitudinal Mediation Analysis with Time-varying Mediators and Exposures, with Application to Survival Outcomes

Zheng, Wenjing; van der Laan, Mark - In: Journal of Causal Inference 5 (2017) 2

Abstract: 1 In this paper, we study the effect of a time-varying exposure mediated by a time-varying intermediate variable. We consider general longitudinal settings, including survival outcomes. At a given time point, the exposure and mediator of interest are influenced by past covariates,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10014610843

gformula: Estimating causal effects in the presence of time-varying confounding or mediation using the g-computation formula

Daniel, Rhian M.; Stavola, Bianca L. De; Cousens, Simon N. - In: Stata Journal 11 (2011) 4, pp. 479-517

This article describes a new command, gformula, that is an implementation of the g-computation procedure. It is used to …

Persistent link: https://ebvufind01.dmz1.zbw.eu/10009391664

Direct Effect Models

Laan, Mark van der; Petersen, Maya - In: International Journal of Biostatistics 4 (2008) 1, pp. 1064-1064

The causal effect of a treatment on an outcome is generally mediated by several intermediate variables. Estimation of the component of the causal effect of a treatment that is not mediated by an intermediate variable (the direct effect of the treatment) is often relevant to mechanistic...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005752616

History-Adjusted Marginal Structural Models and Statically-Optimal Dynamic Treatment Regimens

Laan, Mark van der; Petersen, Maya; Joffe, Marshall - In: International Journal of Biostatistics 1 (2005) 1, pp. 1003-1003

Marginal structural models (MSM) provide a powerful tool for estimating the causal effect of a treatment. These models, introduced by Robins, model the marginal distributions of treatment-specific counterfactual outcomes, possibly conditional on a subset of the baseline covariates. Marginal...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005752619

Data Adaptive Estimation of the Treatment Specific Mean

Wang, Yue; Laan, Mark van der - Berkeley Electronic Press - 2004

of treatment weighted estimators, double robust inverse probability of treatment weighted estimators, and G-computation …

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005751448

Estimation of Direct and Indirect Causal Effects in Longitudinal Studies

Laan, Mark van der; Petersen, Maya - Berkeley Electronic Press - 2004

The causal effect of a treatment on an outcome is generally mediated by several intermediate variables. Estimation of the component of the causal effect of a treatment that is mediated by a given intermediate variable (the indirect effect of the treatment), and the component that is not mediated...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005751451

History-Adjusted Marginal Structural Models and Statically-Optimal Dynamic Treatment Regimes

Laan, Mark van der; Petersen, Maya - Berkeley Electronic Press - 2004

Marginal structural models (MSM) provide a powerful tool for estimating the causal effect of a treatment. These models, introduced by Robins (e.g. Robins (2000a), Robins (2000b), van der Laan and Robins (2002)), model the marginal distributions of treatment-specific counterfactual outcomes,...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005246356