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The Journal of Experimental Education Volume 90, 2022 - Issue 4
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Measurement, Statistics, and Research Design

A Tutorial on Artificial Neural Networks in Propensity Score Analysis

Zachary K. Colliera University of Delaware, Newark, DE, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0003-2526-5120
ORCID Icon &
Walter L. Leiteb University of Florida, Gainesville, FL, USAORCID Iconhttps://orcid.org/0000-0001-7655-5668
ORCID Icon
Pages 1003-1020 | Published online: 11 Jan 2021

Citations (5)

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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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Zachary K. Collier, Kamal Chawla & Olushola Soyoye. Optimizing Imputation for Educational Data: Exploring Training Partition and Missing Data Ratios. The Journal of Experimental Education 0:0, pages 1-21.
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Articles from other publishers (3)

Zachary K. Collier, Minji Kong, Olushola Soyoye, Kamal Chawla, Ann M. Aviles & Yasser Payne. (2023) Deep Learning Imputation for Asymmetric and Incomplete Likert-Type Items. Journal of Educational and Behavioral Statistics 49:2, pages 241-267.
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Jiwoong Yu & Woojoo Lee. (2022) A Critical Review of Propensity Score Matching in Causal Inference. Journal of Health Informatics and Statistics 47:Suppl 1, pages S9-S19.
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Jiwoong Yu & Woojoo Lee. (2022) A Critical Review of Propensity Score Matching in Causal Inference. Journal of Health Informatics and Statistics 47:Suppl 1, pages S9-S19.
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