Results 1 to 10 of about 263,464 (354)

Oversampling and replacement strategies in propensity score matching: a critical review focused on small sample size in clinical settings

BMC Medical Research Methodology, 2021
Background Propensity score matching is a statistical method that is often used to make inferences on the treatment effects in observational studies. In recent years, there has been widespread use of the technique in the cardiothoracic surgery literature
D. Bottigliengo, I. Baldi, C. Lanera, G. Lorenzoni, Jonida Bejko, T. Bottio, V. Tarzia, M. Carrozzini, G. Gerosa, P. Berchialla, D. Gregori   +10 more
semanticscholar   +1 more source

Iterations for Propensity Score Matching in MonetDB [PDF]

, 2020
The amount of data that is stored in databases and must be analyzed is growing fast. Many analytical tasks are based on iterative methods that approximate optimal solutions. Propensity score matching is a technique that is used to reduce bias during cohort building.
Michael H. Böhlen, Oksana Dolmatova, Michael Krauthammer, Alphonse Mariyagnanaseelan, Jonathan Stahl, Timo Surbeck   +5 more
openaire   +1 more source

Understanding the effect of loneliness on unemployment: propensity score matching

BMC Public Health, 2022
Loneliness and unemployment are each detrimental to health and well-being. Recent evidence suggests a potential bidirectional relationship between loneliness and unemployment in working age individuals.
N. Morrish, R. Mujica-Mota, A. Medina-Lara   +2 more
semanticscholar   +1 more source

Training at farmers training centers and its impact on crop productivity and households’ income in Ethiopia: A propensity score matching (PSM) analysis

Heliyon, 2022
The creation and expansion of training and extension networks for rural households are indispensable to develop and improve skills and to increase productivity and income-generating capabilities.
Ketemaw Melkamu Wonde, Abrham Seyoum Tsehay, S. Lemma   +2 more
semanticscholar   +1 more source

HLA-matching with PTCy: a reanalysis of a CIBMTR dataset with propensity score matching and donor age

Blood Advances, 2022
Key Points A reanalysis including donor age and using propensity score matching shows no major differences in survival or relapse. Data sharing and collaborative reanalysis enhance our recognition of the nuances of complex statistical methodologies and ...
A. Ambinder, T. Jain, H. Tsai, M. Horowitz, Richard J. Jones, R. Varadhan   +5 more
semanticscholar   +1 more source

Matching using semiparametric propensity scores [PDF]

Empirical Economics, 2012
This paper considers the application of semiparametric methods to estimate propensity scores or probabilities of program participation, which are central to certain program evaluation methods. To evaluate the practical benefits, we first conduct a Monte Carlo study. Second, we use data from the NSW experiment, CPS, and PSID. We compare treatment effect
Steven Lehrer, Gregory Kordas
openaire   +1 more source

Propensity score matching and inverse probability of treatment weighting to address confounding by indication in comparative effectiveness research of oral anticoagulants.

Journal of Comparative Effectiveness Research, 2020
After decades of warfarin being the only oral anticoagulant (OAC) widely available for stroke prevention in atrial fibrillation, four direct OACs (apixaban, dabigatran, edoxaban and rivaroxaban) were approved after demonstrating noninferior efficacy and ...
V. Allan, S. Ramagopalan, J. Mardekian, A. Jenkins, Xiaoyan Li, Xianying Pan, Xuemei Luo   +6 more
semanticscholar   +1 more source

Propensity score matching and complex surveys [PDF]

Statistical Methods in Medical Research, 2016
Researchers are increasingly using complex population-based sample surveys to estimate the effects of treatments, exposures and interventions. In such analyses, statistical methods are essential to minimize the effect of confounding due to measured covariates, as treated subjects frequently differ from control subjects.
Austin, Peter C, Jembere, Nathaniel, Chiu, Maria   +2 more
openaire   +2 more sources

Applied comparison of large‐scale propensity score matching and cardinality matching for causal inference in observational research

BMC Medical Research Methodology, 2021
Background Cardinality matching (CM), a novel matching technique, finds the largest matched sample meeting prespecified balance criteria thereby overcoming limitations of propensity score matching (PSM) associated with limited covariate overlap, which ...
S. Fortin, S. Johnston, M. Schuemie
semanticscholar   +1 more source

ISOTONIC PROPENSITY SCORE MATCHING

Econometric Theory
We propose a one-to-many matching estimator of the average treatment effect based on propensity scores estimated by isotonic regression. This approach is predicated on the assumption of monotonicity in the propensity score function, a condition that can be justified in many economic applications.
Xu, Mengshan, Otsu, Taisuke
openaire   +4 more sources