Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Groves keynote speaker at MIDAS symposium, Nov 15-16: "Big Data: Advancing Science, Changing the World"

Shaefer says drop child tax credit in favor of universal, direct investment in American children

Buchmueller breaks down partisan views on Obamacare

More News


Gonzalez, Alter, and Dinov win NSF "Big Data Spokes" award for neuroscience network

Post-doc Melanie Wasserman wins dissertation award from Upjohn Institute

ISR kicks off DE&I initiative with lunchtime presentation: Oct 13, noon, 1430 ISR Thompson

U-M ranked #4 in USN&WR's top public universities

More Highlights

Next Brown Bag

Mon, Oct 24 at noon:
Academic innovation & the global public research university, James Hilton

Daniel Almirall photo

Structural Nested Mean Models for Assessing Time-Varying Effect Moderation

Publication Abstract

Almirall, Daniel, Thomas Ten Have, and Susan A. Murphy. 2010. "Structural Nested Mean Models for Assessing Time-Varying Effect Moderation." Biometrics, 66(1): 131-139.

This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect. Intermediate causal effects that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias-variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study.

DOI:10.1111/j.1541-0420.2009.01238.x (Full Text)

PMCID: PMC2875310. (Pub Med Central)

Country of focus: United States of America.

Browse | Search : All Pubs | Next