The method of inverse probability weighting (henceforth, weighting) can be used to adjust for measured confounding and selection bias under the four assumptions of consistency, exchangeability, positivity, and no misspecification of the model used to estimate weights. In recent years, several published estimates of the effect of time-varying exposures have been based on weighted estimation of the parameters of marginal structural models because, unlike standard statistical methods, weighting can appropriately adjust for measured time-varying confounders affected by prior exposure. As an example, the authors describe the last three assumptions using the change in viral load due to initiation of antiretroviral therapy among 918 human immunodeficiency virus-infected US men and women followed for a median of 5.8 years between 1996 and 2005. The authors describe possible tradeoffs that an epidemiologist may encounter when attempting to make inferences. For instance, a tradeoff between bias and precision is illustrated as a function of the extent to which confounding is controlled. Weight truncation is presented as an informal and easily implemented method to deal with these tradeoffs. Inverse probability weighting provides a powerful methodological tool that may uncover causal effects of exposures that are otherwise obscured. However, as with all methods, diagnostics and sensitivity analyses are essential for proper use.

S. R. Cole

M. A. Hernan

American Journal of Epidemiology

AMERICAN JOURNAL OF EPIDEMIOLOGY 是历史最悠久，也是主要的流行病学期刊之一，致力于发表流行病学研究领域的实证研究结果、观点文章和方法论发展。使用流行病学数据的人，包括公共卫生工作者和临床医生。

The American Journal of Epidemiology is one of the oldest and most prominent journals in the field of epidemiology, dedicated to publishing empirical research findings, opinion articles, and methodological developments in epidemiology. Its readership includes public health professionals and clinicians who utilize epidemiological data.

《American Journal of Epidemiology》是历史最悠久且最重要的流行病学期刊之一，专注于发表流行病学领域的实证研究结果、观点文章和方法论的发展。该期刊的读者包括公共卫生工作者和临床医生，他们利用流行病学数据进行研究和实践。

Constructing Inverse Probability Weights for Marginal Structural Models

The authors describe possible tradeoffs that an epidemiologist may encounter when attempting to make inferences and weight truncation is presented as an informal and easily implemented method to deal with these tradeoffs.

Category	Quartile
医学	2
医学, 公共卫生、环境卫生与职业卫生	2

Constructing Inverse Probability Weights for Marginal Structural Models

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Category	Quartile
PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH	1