Biostatistics Group Seminar 17th Jan

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Biostatistics Group Seminar 17th Jan

Postby rsc97 » Fri Jan 11, 2019 3:21 pm

Title: Estimating causal effects of time-varying exposures using observational data: What can we do using standard regression methods.

Speaker: Dr Ruth Keogh, Department of Medical Statistics, London School of Hygiene & Tropical Medicine.

Date: Thursday 17th January 12:00-13:00

Venue: Dinwoodie Lecture Theatre, David Weatherall Building
https://www.keele.ac.uk/connect/howtofi ... colour.pdf

Abstract: This talk will focus on estimation of causal effects from observational studies with longitudinal repeated measures of exposures and outcomes, such as when individuals are observed at repeated visits, which is a common problem in epidemiology. Interest may lie in studying the ‘total effect’ of an exposure at a given time on a concurrent or subsequent outcome, or the effect of a pattern of exposures over time on a subsequent outcome. It is sometimes not appreciated that standard regression methods can be used, even in the presence of time-dependent confounding, to estimate the total effect of an exposure on a subsequent outcome by controlling appropriately for prior exposures, outcomes and time-varying covariates. I will discuss the important considerations for estimating causal total exposure effects using standard methods, and make comparisons with alternative approaches from the causal inference literature, in particular using marginal structural models fitted by inverse probability weighting. I will give an example in which we have used patient registry data to study the causal effect of a treatment used in cystic fibrosis on lung function.

The talk will be partly based on recent work in the paper:
Keogh, Daniel, VanderWeele, Vansteelandt. Analysis of longitudinal studies with repeated outcome measures: adjusting for time-dependent confounding using conventional methods. Am J Epidemiol 2017; https://doi.org/10.1093/aje/kwx311.
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