I read with great interest the recent Journal article by Nandi et al. (1) on the role of neighborhood poverty as a potential determinant of injection cessation among injection drug users. The authors fitted and contrasted 4 logistic regression models: "crude," "baseline adjusted," "fully adjusted," and one based on inverse-probability weighting (IPW). The results obtained from the IPW model were taken to be valid, whereas those from the other 3 models-including, notably, the "fully adjusted" one-were taken to be biased. Specifically, in the Discussion section of their article, the authors state the following: "These divergent results suggest that use of traditional regression to handle confounding in neighborhood effects studies may induce bias because the individual-level characteristics frequently adjusted for may be time-dependent covariates affected by prior exposure" (1, p. 395).
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