[Sds-seminars] CMIPS-YCAS Working Group Presentation by Gang Xu, PhD, April 28 at 12:00 PM – “A doubly robust machine learning method for causal inference, correcting for measurement error in the exposure of interest and confounders”.

[Spiegelman, Donna]

Dear Colleagues,

Our presenter on 4/28 at 12 noon is Dr. Gang Xu, who is currently a postdoc associate at the Department of Biostatistics at YSPH. His talk title and abstract are below. Look forward to seeing you all.

Title: A doubly robust machine learning method for causal inference, correcting for measurement error in the exposure of interest and confounders

Abstract: Measures of air pollution such as PM2.5 and its chemical components are commonly obtained from nearest monitors, without personal exposure accurately assessed in epidemiological studies. Measurement error can lead to substantial bias in the estimated effect of air pollution on health outcomes, especially when interest is in assessing the independent impact of correlated multi-pollutant constituents of air pollution. In this study, we focus on the effect assessment of one chemical component in the presence of other correlated components of PM2.5, where all chemical components are subject to measurement error, also possibly correlated. We assume a linear Berkson-like measurement error model fit using generalized estimating equations (GEE) in an external validation study, and extend a doubly robust machine learning (DML) approach (Chernozhukov et al., 2018), correcting for measurement error, to estimate the effect of interest in the main study. We derive the statistical properties of the DML estimator with measurement error correction. Simulation results showed that the proposed estimator had reduced bias and the coverage rate close to or above the nominal level across all simulation settings. We are currently applying this method to assess the effect of multi-pollutant air pollution PM2.5 on cognitive function in the Nurses’ Health Study.




-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.yale.edu/pipermail/sds-seminars/attachments/20230424/ec99cc4b/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: CMIPS_YCAS Working Group - April 2023.ics
Type: text/calendar
Size: 49607 bytes
Desc: CMIPS_YCAS Working Group - April 2023.ics
URL: <http://mailman.yale.edu/pipermail/sds-seminars/attachments/20230424/ec99cc4b/attachment.ics>