Results 1 to 10 of about 3,395 (67)

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, Delia North, Temesgen Zewotir   +2 more
doaj   +1 more source

Depressive symptoms among people under COVID-19 quarantine or self-isolation in Korea: a propensity score matching analysis

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

Evaluating the Performance of High-Dimensional Propensity Scores Compared with Standard Propensity Scores for Comparing Antihypertensive Therapies in the CPRD GOLD Database

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   +1 more source

The impact of moderator by confounder interactions in the assessment of treatment effect modification: a simulation study

BMC Medical Research Methodology, 2022
Background When performed in an observational setting, treatment effect modification analyses should account for all confounding, where possible. Often, such studies only consider confounding between the exposure and outcome.
Antonia Mary Marsden, William G. Dixon, Graham Dunn, Richard Emsley   +3 more
doaj   +1 more source

Evaluating Uses of Deep Learning Methods for Causal Inference

IEEE Access, 2022
Logistic regression (LR) is a popular method that is used for estimating causal effects in observational studies using propensity scores. We examine the use of deep learning models such as the deep neural network (DNN), PropensityNet (PN), convolutional ...
Albert Whata, Charles Chimedza
doaj   +1 more source

Head to head comparison of the propensity score and the high-dimensional propensity score matching methods

BMC Medical Research Methodology, 2016
Background Comparative performance of the traditional propensity score (PS) and high-dimensional propensity score (hdPS) methods in the adjustment for confounding by indication remains unclear.
Jason R. Guertin, Elham Rahme, Colin R. Dormuth, Jacques LeLorier   +3 more
doaj   +1 more source

Propensity Score Matching in Non-Interventional Studies: A Step-by-Step Guide for Clinicians and Researchers [PDF]

Iranian Journal of Medical Sciences
Selection bias occurs when a study’s sample is not representative of the entire population, which can lead to incorrect conclusions.
Saeedeh Pourahmad, Farzan Madadizadeh
doaj   +1 more source

Evaluating effectiveness of payments for forest ecosystem services by propensity scores analysis [PDF]

Ekonomika Poljoprivrede (1979), 2020
The Vietnamese Government have been implementing the Payment for Forest Ecosystem Service (PFES) since 2008 with the aim of both improving natural forest status and enhancing income for mountainous community.
Nguyen Huynh Tan, Hung Nguyen Hoang
doaj  

Is the use of bipolar hemiarthroplasty over monopolar hemiarthroplasty justified? A propensity score-weighted analysis of a multicentre randomized controlled trial

Bone & Joint Open, 2023
Aims: Using data from the Hip Fracture Evaluation with Alternatives of Total Hip Arthroplasty versus Hemiarthroplasty (HEALTH) trial, we sought to determine if a difference in functional outcomes exists between monopolar and bipolar hemiarthroplasty (HA).
Marianne Comeau-Gauthier, Sofia Bzovsky, Daniel Axelrod, Rudolf W. Poolman, Frede Frihagen, Mohit Bhandari, Emil Schemitsch, Sheila Sprague, On behalf of the HEALTH investigators   +8 more
doaj   +1 more source

Propensity Scores: A Practical Introduction Using R

Journal of MultiDisciplinary Evaluation, 2015
Background: This paper provides an introduction to propensity scores for evaluation practitioners. Purpose: The purpose of this paper is to provide the reader with a conceptual and practical introduction to propensity scores, matching using propensity ...
Antonio Olmos, Priyalatha Govindasamy
doaj   +1 more source