Results 1 to 10 of about 130,821 (302)
Evaluating the Performance of High-Dimensional Propensity Scores Compared with Standard Propensity Scores for Comparing Antihypertensive Therapies in the CPRD GOLD Database [PDF]
Cardiology and Therapy, 2023 Introduction Propensity score (PS) matching is widely used in medical record studies to create balanced treatment groups, but relies on prior knowledge of confounding factors.
Virginie Simon, Jade Vadel
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
Weighting Regressions by Propensity Scores [PDF]
Evaluation Review, 2008 Regressions can be weighted by propensity scores in order to reduce bias. However, weighting is likely to increase random error in the estimates, and to bias the estimated standard errors downward, even when selection mechanisms are well understood. Moreover, in some cases, weighting will increase the bias in estimated causal parameters.
David A Freedman, Richard A Berk
exaly +4 more sources
A Boosting Algorithm for Estimating Generalized Propensity Scores with Continuous Treatments
Journal of Causal Inference, 2015 In this article, we study the causal inference problem with a continuous treatment variable using propensity score-based methods. For a continuous treatment, the generalized propensity score is defined as the conditional density of the treatment-level ...
Zhu Yeying +2 more
doaj +2 more sources
Optimal hyperparameter tuning of random forests for estimating causal treatment effects [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2021 Recent studies have expanded the focus of machine learning methods like random forests beyond prediction. They have found utility in the area of causal inference by using it to estimate propensity scores.
Lateef Amusa +2 more
doaj +1 more source
Frontiers in Psychiatry, 2023 IntroductionThis study aims to determine the effect of COVID-19-related hospital isolation or self-isolation on depression using the propensity score matching method.MethodsData on 217,734 participants were divided into groups based on whether or not ...
Hyeon Sik Chu, Kounseok Lee
doaj +1 more source
JAMA, 2015 Two recent studies published in JAMA involved the analysis of observational data to estimate the effect of a treatment on patient outcomes. In the study by Roze et al,1 a large observational data set was analyzed to estimate the relationship between early echocardiography screening for patent ductus arteriosus and mortality among preterm infants.
Jason S, Haukoos, Roger J, Lewis
openaire +2 more sources
Demystifying propensity scores [PDF]
British Journal of Anaesthesia, 2014 Increasing availability of large clinical data sets is driving a proliferation of observational epidemiology studies in perioperative care. This wealth of data must be judged both on its inherent quality and the statistical techniques used to analyse the data set.
G N, Okoli, R D, Sanders, P, Myles
openaire +2 more sources