Results 31 to 40 of about 2,231,738 (318)
Rerandomization to Balance Tiers of Covariates [PDF]
Journal of the American Statistical Association, 2015 When conducting a randomized experiment, if an allocation yields treatment groups that differ meaningfully with respect to relevant covariates, groups should be rerandomized. The process involves specifying an explicit criterion for whether an allocation is acceptable, based on a measure of covariate balance, and rerandomizing units until an acceptable
Kari Lock, Morgan, Donald B, Rubin
openaire +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
The role of covariate balance in observational studies
Naval Research Logistics (NRL), 2017 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jason J. Sauppe, S. Jacobson
semanticscholar +3 more sources
Covariate Balancing Propensity Score [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2013 SummaryThe propensity score plays a central role in a variety of causal inference settings. In particular, matching and weighting methods based on the estimated propensity score have become increasingly common in the analysis of observational data. Despite their popularity and theoretical appeal, the main practical difficulty of these methods is that ...
Imai, Kosuke, Ratkovic, Marc
openaire +1 more source
Quasi-rerandomization for observational studies
BMC Medical Research Methodology, 2023 Background In the causal analysis of observational studies, covariates should be carefully balanced to approximate a randomized experiment. Numerous covariate balancing methods have been proposed for this purpose.
Hengtao Zhang, Wen Su, Guosheng Yin
doaj +1 more source
Covariant balance laws in continua with microstructure [PDF]
Reports on Mathematical Physics, 2009 The purpose of this paper is to extend the Green-Naghdi-Rivlin balance of energy method to continua with microstructure. The key idea is to replace the group of Galilean transformations with the group of diffeomorphisms of the ambient space. A key advantage is that one obtains in a natural way all the needed balance laws on both the macro and micro ...
Yavari, Arash, Marsden, Jerrold E.
openaire +3 more sources
Covariate balancing based on kernel density estimates for controlled experiments
Statistical Theory and Related Fields, 2021 Controlled experiments are widely used in many applications to investigate the causal relationship between input factors and experimental outcomes. A completely randomised design is usually used to randomly assign treatment levels to experimental units ...
Yiou Li, Lulu Kang, Xiao Huang
doaj +1 more source
, 2022 Covariate balance: unweighted vs overlap weighted cohorts.
Adelino Leite-Moreira (3376820) +2 more
core +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
Covariate balance of PSM sample.
, 2022 Covariate balance of PSM sample.
Bofu Zhang (13132780) +1 more
core +1 more source