Results 271 to 280 of about 1,742,420 (301)

Review of inverse probability weighting for dealing with missing data

Statistical Methods in Medical Research, 2011
The simplest approach to dealing with missing data is to restrict the analysis to complete cases, i.e. individuals with no missing values. This can induce bias, however. Inverse probability weighting (IPW) is a commonly used method to correct this bias. It is also used to adjust for unequal sampling fractions in sample surveys. This article is a review
Shaun R, Seaman, Ian R, White
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Variable selection using inverse probability of censoring weighting

Statistical Methods in Medical Research, 2023
In this article, we propose two variable selection methods for adjusting the censoring information for survival times, such as the restricted mean survival time. To adjust for the influence of censoring, we consider an inverse probability of censoring weighted for subjects with events. We derive a least absolute shrinkage and selection operator (lasso)
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Constructing Inverse Probability Weights for Continuous Exposures

Epidemiology, 2014
Inverse 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, Erica E M, Moodie, Nathalie, Auger, Jay S, Kaufman   +3 more
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Methods for Inverse Probability of Attrition Weighting

2020
In 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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Estimation of attributable fractions using inverse probability weighting

Statistical Methods in Medical Research, 2010
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.
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On π-inverse weighting versus best linear unbiased weighting in probability sampling

Biometrika, 1980
SUMMARY 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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A note on convergence of calibration weights to inverse probability weights

Statistica Neerlandica
AbstractRecently, nonresponse rates in sample surveys have been increasing. Nonresponse bias is a serious concern in the analysis of sample surveys. The calibration and propensity score methods are used to adjust nonresponse bias. The propensity score method uses the weights of the inverse probability of response. The inverse probability of response is
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An Adaptive Inverse-Distance Weighting Interpolation Method Considering Spatial Differentiation in 3D Geological Modeling

Geosciences (Switzerland), 2021
Cuiying Zhou, Zhen Liu, Weihua Ming
exaly  

Inverse probability weighted methods

2008
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Robust Inference Using Inverse Probability Weighting

Journal of the American Statistical Association, 2020
Xinwei Ma, Jingshen Wang
exaly