Using propensity scores to estimate effects of treatment initiation decisions: State of the science.
Sign Up to like & getrecommendations! Published in 2020 at "Statistics in medicine"
DOI: 10.1002/sim.8866
Abstract: Confounding can cause substantial bias in nonexperimental studies that aim to estimate causal effects. Propensity score methods allow researchers to reduce bias from measured confounding by summarizing the distributions of many measured confounders in a… read more here.
Keywords: estimate effects; scores estimate; treatment; using propensity ... See more keywords
Last Nail in the Coffin for Propensity Scores in Observational Cardiovascular Studies?
Sign Up to like & getrecommendations! Published in 2017 at "Journal of the American College of Cardiology"
DOI: 10.1016/j.jacc.2017.01.072
Abstract: We have read with interest the thorough comparative analysis and review on propensity score analysis and inverse probability of treatment weighting analysis reported in the Journal by Elze et al. [(1)][1]. They compared the performance of… read more here.
Keywords: coffin propensity; analysis; nail coffin; last nail ... See more keywords
The impact of confounder selection in propensity scores when applied to prospective cohort studies in pregnancy.
Sign Up to like & getrecommendations! Published in 2018 at "Reproductive toxicology"
DOI: 10.1016/j.reprotox.2018.04.003
Abstract: Our work was motivated by small cohort studies on the risk of birth defects in infants born to pregnant women exposed to medications. We controlled for confounding using propensity scores (PS). The extremely rare events… read more here.
Keywords: impact confounder; propensity scores; cohort studies; selection ... See more keywords
iBitter-SCM: Identification and characterization of bitter peptides using a scoring card method with propensity scores of dipeptides.
Sign Up to like & getrecommendations! Published in 2020 at "Genomics"
DOI: 10.1016/j.ygeno.2020.03.019
Abstract: In general, hydrolyzed proteins, plant-derived alkaloids and toxins displays unpleasant bitter taste. Thus, the perception of bitter taste plays a crucial role in protecting animals from poisonous plants and environmental toxins. Therapeutic peptides have attracted… read more here.
Keywords: propensity scores; ibitter scm; bitter peptides;
SCMRSA: a New Approach for Identifying and Analyzing Anti-MRSA Peptides Using Estimated Propensity Scores of Dipeptides
Sign Up to like & getrecommendations! Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c04305
Abstract: Staphylococcus aureus is deemed to be one of the major causes of hospital and community-acquired infections, especially in methicillin-resistant S. aureus (MRSA) strains. Because antimicrobial peptides have captured attention as novel drug candidates due to… read more here.
Keywords: peptides using; propensity scores; anti mrsa; mrsa peptides ... See more keywords
Addressing Extreme Propensity Scores via the Overlap Weights
Sign Up to like & getrecommendations! Published in 2019 at "American Journal of Epidemiology"
DOI: 10.1093/aje/kwy201
Abstract: The popular inverse probability weighting method in causal inference is often hampered by extreme propensity scores, resulting in biased estimates and excessive variance. A common remedy is to trim patients with extreme scores (i.e., remove… read more here.
Keywords: addressing extreme; extreme propensity; scores via; overlap weights ... See more keywords
Higher Moments for Optimal Balance Weighting in Causal Estimation
Sign Up to like & getrecommendations! Published in 2022 at "Epidemiology"
DOI: 10.1097/ede.0000000000001481
Abstract: We expand upon a simulation study that compared three promising methods for estimating weights for assessing the average treatment effect on the treated for binary treatments: generalized boosted models, covariate-balancing propensity scores, and entropy balance.… read more here.
Keywords: propensity scores; higher moments; balance; balancing propensity ... See more keywords
Evaluating Uses of Deep Learning Methods for Causal Inference
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2021.3140189
Abstract: Logistic regression 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),… read more here.
Keywords: propensity scores; causal inference; logistic regression; deep learning ... See more keywords
Towards greater transparency in neurodevelopmental disorders research: use of a proposed workflow and propensity scores to facilitate selection of matched groups
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Neurodevelopmental Disorders"
DOI: 10.1186/s11689-020-09321-6
Abstract: Background Matching is one commonly utilized method in quasi-experimental designs involving individuals with neurodevelopmental disorders (NDD). This method ensures two or more groups (e.g., individuals with an NDD versus neurotypical individuals) are balanced on pre-existing… read more here.
Keywords: research; selection; matched groups; propensity scores ... See more keywords