Literature DB >> 20223785

Estimation of attributable fractions using inverse probability weighting.

Arvid Sjölander1.   

Abstract

The attributable fraction is commonly used in epidemiology to quantify the impact of an exposure on a disease. Several estimation methods have been suggested in the literature, including maximum likelihood estimation. In this article we propose an additional estimation method, based on inverse probability weighting. This method is particularly useful when a model for the exposure distibution can be well specified. We carry out a simulation study to examine the performance of the inverse probability weighted estimator, and to compare it to the maximum likelihood estimator.

Mesh:

Year:  2010        PMID: 20223785     DOI: 10.1177/0962280209349880

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  4 in total

1.  From exposures to population interventions: pregnancy and response to HIV therapy.

Authors:  Daniel Westreich
Journal:  Am J Epidemiol       Date:  2014-02-25       Impact factor: 4.897

2.  An Illustration of Inverse Probability Weighting to Estimate Policy-Relevant Causal Effects.

Authors:  Jessie K Edwards; Stephen R Cole; Catherine R Lesko; W Christopher Mathews; Richard D Moore; Michael J Mugavero; Daniel Westreich
Journal:  Am J Epidemiol       Date:  2016-07-28       Impact factor: 4.897

3.  Using a Marginal Structural Model to Design a Theory-Based Mass Media Campaign.

Authors:  Hiromu Nishiuchi; Masataka Taguri; Yoshiki Ishikawa
Journal:  PLoS One       Date:  2016-07-21       Impact factor: 3.240

4.  Graphical comparisons of relative disease burden across multiple risk factors.

Authors:  John Ferguson; Neil O'Leary; Fabrizio Maturo; Salim Yusuf; Martin O'Donnell
Journal:  BMC Med Res Methodol       Date:  2019-09-11       Impact factor: 4.615

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.