Results 11 to 20 of about 1,792,800 (248)
Using Propensity Scores for Causal Inference: Pitfalls and Tips [PDF]
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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Beyond balance: propensity scores and causal reasoning [PDF]
Korean Journal of AnesthesiologyEunjin Ahn
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Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments [PDF]
BMC Bioinformatics, 2023 Background We developed a novel approach to minimize batch effects when assigning samples to batches. Our algorithm selects a batch allocation, among all possible ways of assigning samples to batches, that minimizes differences in average propensity ...
Patrick M. Carry +9 more
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Instability of estimation results based on caliper matching with propensity scores [PDF]
PLoS ONECaliper matching is often used to adjust for confounding biases in observational studies. This method with random order matching allows for the cherry-picking of the analysis results to suit the analyst's convenience.
Kazushi Maruo +3 more
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Controlling for Differential Regression-To-The-Mean via Propensity Scores: A Simulation Study [PDF]
Clinical Epidemiology, 2023 Chase D Latour,1,2 Leah J McGrath,2 Mary Clouser,3 Carrie Nielson,3 Ying Yu,2 Akhila Balasubramanian,3 Alexander Breskin,1,2 M Alan Brookhart2,4 1Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; 2Target RWE ...
Latour CD +7 more
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A comparison of two methods of estimating propensity scores after multiple imputation
, 2011 In many observational studies, analysts estimate treatment effects using propensity scores, e.g., by matching or sub classifying on the scores. When some values of the covariates are missing, analysts can use multiple imputation to fill in the missing ...
Reiter, Jerome P. +4 more
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Estimating propensity scores with missing covariate data using general location mixture models
, 2009 In many observational studies, researchers estimate causal effects using propensity scores, e.g., by matching or sub-classifying on the scores. Estimation of propensity scores is complicated when some values of the covariates aremissing.
Reiter, Jerome P. +3 more
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Propensity scores common support area.
, 2021 Distribution of propensity scores across beneficiaries and non-beneficiaries. (TIF)
Poliana Rebouças (10901591) +11 more
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Cancer Medicine, 2022 Background Patients diagnosed with cancer often experience considerable challenges with mental health, and those who had more intense psychiatric care prior to their cancer diagnosis have a higher risk of mortality.
Rinku Sutradhar +3 more
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