Regression‐with‐residuals estimation of marginal effects: a method of adjusting for treatment‐induced confounders that may also be effect modifiers

Geoffrey T. Wodtke, Zahide Alaca and Xiang Zhou

Journal of the Royal Statistical Society Series A, 2020, vol. 183, issue 1, 311-332

Abstract: When making causal inferences, treatment‐induced confounders complicate analyses of time‐varying treatment effects. Conditioning on these variables naively to estimate marginal effects may inappropriately block causal pathways and may induce spurious associations between the treatment and the outcome, leading to bias. Although several methods for estimating marginal effects avoid these complications, including inverse probability of treatment weighted estimation of marginal structural models as well as g‐ and regression‐with‐residuals estimation of highly constrained structural nested mean models, each suffers from a set of non‐trivial limitations, among them an inability to accommodate effect modification. In this study, we adapt the method of regression with residuals to estimate marginal effects with a set of moderately constrained structural nested mean models that easily accommodate several types of treatment‐by‐confounder interaction. With this approach, the confounders at each time point are first residualized with respect to the observed past, which involves centring them at their estimated means given prior treatments and confounders. The outcome is then regressed on all prior variables, including a set of treatment‐by‐confounder interaction terms, with these residuals substituted for the untransformed confounders both as ‘main effects’ and as part of any interaction terms. Through a series of simulation experiments and empirical examples, we show that this approach outperforms other methods for estimating the marginal effects of time‐varying treatments.

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.1111/rssa.12497

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssa:v:183:y:2020:i:1:p:311-332

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-985X

Access Statistics for this article

Journal of the Royal Statistical Society Series A is currently edited by A. Chevalier and L. Sharples

More articles in Journal of the Royal Statistical Society Series A from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().