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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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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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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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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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A note on convergence of calibration weights to inverse probability weights
Statistica NeerlandicaAbstractRecently, 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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Active learning for regression by inverse distance weighting
Information Sciences, 2023Alberto Bemporad
exaly
Robust Inference Using Inverse Probability Weighting
Journal of the American Statistical Association, 2020Xinwei Ma, Jingshen Wang
exaly