Citations (14)
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Read on this site (2)
Zachary K. Collier, Walter L. Leite & Haobai Zhang. (2023) Estimating propensity scores using neural networks and traditional methods: a comparative simulation study. Communications in Statistics - Simulation and Computation 52:9, pages 4545-4560.
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M. Silan, B. Arpino & G. Boccuzzo. (2021) Evaluating inverse propensity score weighting in the presence of many treatments. An application to the estimation of the neighbourhood effect. Journal of Statistical Computation and Simulation 91:4, pages 836-859.
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Articles from other publishers (12)
Christopher Huong & Denver M.Y. Brown. (2024) Associations between physical activity and subcategories of mental health: A propensity score analysis among a global sample of 341,956 adults. Mental Health and Physical Activity 26, pages 100586.
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Luis Castro, María del Mar Rueda, Carmen Sánchez-Cantalejo, Ramón Ferri & Andrés Cabrera-León. (2024) Calibration and XGBoost reweighting to reduce coverage and non-response biases in overlapping panel surveys: application to the Healthcare and Social Survey. BMC Medical Research Methodology 24:1.
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Nuno Castro Lopes & Luís Cavique. 2023. Philosophy of Artificial Intelligence and Its Place in Society. Philosophy of Artificial Intelligence and Its Place in Society
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Colman Humphrey, Ryan Gross, Dylan S. Small & Shane T. Jensen. (2023) Using predictability to improve matching of urban locations in Philadelphia. The Annals of Applied Statistics 17:3.
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Leandro Pereira Garcia, Ione Jayce Ceola Schneider, Cesar de Oliveira, Eliane Traebert & Jefferson Traebert. (2023) What is the impact of national public expenditure and its allocation on neonatal and child mortality? A machine learning analysis. BMC Public Health 23:1.
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Sheryll Dimanlig-Cruz, Daniel J. Corsi, Andrea Lanes, Lynn Meng, Qun Miao, Mark Walker & Deshayne B. Fell. (2023) Perinatal and pediatric outcomes associated with the use of fertility treatment: a population-based retrospective cohort study in Ontario, Canada. BMC Pregnancy and Childbirth 23:1.
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Shu Yang, Peipei Du, Xixi Feng, Daihai He, Yaolong Chen, Linda L. D. Zhong, Xiaodong Yan & Jiawei Luo. (2023) Propensity score analysis with missing data using a multi-task neural network. BMC Medical Research Methodology 23:1.
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Shuxin Dong, Yara Abu-Awad, Anna Kosheleva, Kelvin C. Fong, Petros Koutrakis & Joel D. Schwartz. (2022) Maternal exposure to black carbon and nitrogen dioxide during pregnancy and birth weight: Using machine-learning methods to achieve balance in inverse-probability weights. Environmental Research 211, pages 112978.
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Luis Castro-Martín, María del Mar Rueda, Ramón Ferri-García & César Hernando-Tamayo. (2021) On the Use of Gradient Boosting Methods to Improve the Estimation with Data Obtained with Self-Selection Procedures. Mathematics 9:23, pages 2991.
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Xiliang Lin, Tho Ngoc Le, Carlos Carrion & Zenan Wang. (2021) Turning a Curse into a Blessing: A General Approach to Resolve Endogeneity Problem in Data-Rich Environment. Turning a Curse into a Blessing: A General Approach to Resolve Endogeneity Problem in Data-Rich Environment.
Arni S.R. Srinivasa Rao & Michael P. Diamond. (2020) Deep Learning of Markov Model-Based Machines for Determination of Better Treatment Option Decisions for Infertile Women. Reproductive Sciences 27:2, pages 763-770.
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Shu Yang, Peipei Du, Daihai He, Yaolong Chen, Linda Zhong, Xixi Feng, Xiaodong Yan & Jiawei Luo. (2022) Propensity Score Analysis with Missing Data Using a Multi-Task Neural Networks. SSRN Electronic Journal.
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