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Estimation of attributable fractions using inverse probability weighting
Statistical Methods in Medical Research, 2010The 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.
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Constructing inverse probability weights for institutional comparisons in healthcare
Statistics in Medicine, 2020In comparing quality of care between hospitals, disease‐specific quality indicators measure structural, process, or outcome elements related to the care of a particular condition. Such comparisons can be framed in terms of causal contrasts, answering the question of whether a patient (or a population of patients on average) would receive different care
Thai‐Son Tang +4 more
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Augmented inverse probability weighted fractional imputation in quantile regression
Pharmaceutical Statistics, 2020SummaryBy employing all the observed information and the optimal augmentation term, we propose an augmented inverse probability weighted fractional imputation method (AFI) to handle covariates missing at random in quantile regression. Compared with the existing completely case analysis, inverse probability weighting, multiple imputation and fractional ...
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Constructing Inverse Probability Weights for Continuous Exposures
Epidemiology, 2014Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance.
Ashley I, Naimi +3 more
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Methods for Inverse Probability of Attrition Weighting
2020In this paper, we examine methods for Inverse Probability of Attrition Weighting (IPAW) in a cohort study. Such longitudinal studies often suffer from attrition bias when participants fail to attend follow up visits. IPAW is a common strategy to address attrition bias which allows for unbiased estimation of causal effects.
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On π-inverse weighting versus best linear unbiased weighting in probability sampling
Biometrika, 1980SUMMARY This paper deals with two schemes, it-inverse weights and best linear unbiased weights, for weighting of observations drawn by unequal probability sampling methods. The context is that of constructing an asymptotically design-unbiased estimate of the mean of a finite population.
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Augmented Inverse Probability Weighted Estimator for Cox Missing Covariate Regression
Biometrics, 2001Summary.This article investigates an augmented inverse selection probability weighted estimator for Cox regression parameter estimation when covariate variables are incomplete. This estimator extends the Horvitz and Thompson (1952,Journal of the American Statistical Association47, 663–685) weighted estimator.
Wang, C. Y., Chen, Hua Yun
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Investigation of selection bias using inverse probability weighting
European Journal of Epidemiology, 2007In 1999-2001, university graduates in the city of Pamplo na, Spain were invited to participate in a study of cardio vascular diseases and motor vehicle injuries [1]. This selection prevented generalization of the results to the population of Pamplona.
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An introduction to inverse probability of treatment weighting in observational research
CKJ: Clinical Kidney Journal, 2022Nicholas C Chesnaye +2 more
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