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Inverse probability weighting with error-prone covariates [PDF]
Biometrika, 2013 Inverse probability-weighted estimators are widely used in applications where data are missing due to nonresponse or censoring and in the estimation of causal effects from observational studies. Current estimators rely on ignorability assumptions for response indicators or treatment assignment and outcomes being conditional on observed covariates which
Daniel F. McCaffrey +2 more
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Journal of Biostatistics and Epidemiology, 2020 Introduction: Missing values are frequently seen in data sets of research studiesespecially in medical studies.Therefore, it is essential that the data, especially in medical research should evaluate in terms of the structure of missingness.This study ...
Freshteh Osmani, Ebrahim Hajizadeh
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Inverse probability weighting for clustered nonresponse [PDF]
Biometrika, 2011 Correlated nonresponse within clusters arises in certain survey settings. It is often represented by a random effects model and assumed to be cluster-specific nonignorable, in the sense that survey and nonresponse outcomes are conditionally independent given cluster-level random effects.
Chris J. Skinner, Julia D'Arrigo
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Understanding Marginal Structural Models for Time-Varying Exposures: Pitfalls and Tips
Journal of Epidemiology, 2020 Epidemiologists are increasingly encountering complex longitudinal data, in which exposures and their confounders vary during follow-up. When a prior exposure affects the confounders of the subsequent exposures, estimating the effects of the time-varying
Tomohiro Shinozaki, Etsuji Suzuki
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Differences in Abdominal Body Composition According to Glycemic Status: An Inverse Probability Treatment Weighting Analysis [PDF]
Endocrinology and Metabolism, 2021 Background Several studies have reported that abdominal fat and muscle changes occur in diabetic patients. However, there are few studies about such changes among prediabetic patients.
Seungbong Han +6 more
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Variance estimation in inverse probability weighted Cox models
Biometrics, 2020 AbstractInverse probability weighted Cox models can be used to estimate marginal hazard ratios under different point treatments in observational studies. To obtain variance estimates, the robust sandwich variance estimator is often recommended to account for the induced correlation among weighted observations.
Di Shu +3 more
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Application of inverse probability weights in survival analysis [PDF]
Journal of Nuclear Cardiology, 2015 Suppose that a researcher is interested in comparing two ‘‘treatments’’—A and B—and how the treatment affects an outcome of interest. The ideal study design would be to conduct a randomized trial where treatment assignment is randomly assigned. The random treatment assignment aims to make the subjects between the two treatments similar, i.e., it aims ...
Guoqiao, Wang, Inmaculada, Aban
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BMC Medical Informatics and Decision Making, 2020 Background and objectives Height and weight data from electronic health records are increasingly being used to estimate the prevalence of childhood obesity.
Carmen Sayon-Orea +9 more
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Using Propensity Scores for Causal Inference: Pitfalls and Tips
Journal of Epidemiology, 2021 Methods based on propensity score (PS) have become increasingly popular as a tool for causal inference. A better understanding of the relative advantages and disadvantages of the alternative analytic approaches can contribute to the optimal choice and ...
Koichiro Shiba, Takuya Kawahara
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Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, 2021 Background This study compared the efficacy and safety between catheter‐directed thrombolysis (CDT) and systemic thrombolysis for patients with acute pulmonary embolism (PE) with midterm follow‐up.
Donna Shu‐Han Lin +4 more
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