Correlated Cluster-Based Randomized Experiments: Robust Variance Minimization
Author
Abstract
Suggested Citation
DOI: 10.1287/mnsc.2021.02741
Download full text from publisher
References listed on IDEAS
- Eckles Dean & Karrer Brian & Ugander Johan, 2017. "Design and Analysis of Experiments in Networks: Reducing Bias from Interference," Journal of Causal Inference, De Gruyter, vol. 5(1), pages 1-23, March.
- Ramesh Johari & Hannah Li & Inessa Liskovich & Gabriel Y. Weintraub, 2022. "Experimental Design in Two-Sided Platforms: An Analysis of Bias," Management Science, INFORMS, vol. 68(10), pages 7069-7089, October.
- Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
- Ruomeng Cui & Jun Li & Dennis J. Zhang, 2020. "Reducing Discrimination with Reviews in the Sharing Economy: Evidence from Field Experiments on Airbnb," Management Science, INFORMS, vol. 66(3), pages 1071-1094, March.
- David Holtz & Sinan Aral, 2020. "Limiting Bias from Test-Control Interference in Online Marketplace Experiments," Papers 2004.12162, arXiv.org.
- Iavor Bojinov & David Simchi-Levi & Jinglong Zhao, 2023. "Design and Analysis of Switchback Experiments," Management Science, INFORMS, vol. 69(7), pages 3759-3777, July.
- Hudgens, Michael G. & Halloran, M. Elizabeth, 2008. "Toward Causal Inference With Interference," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 832-842, June.
- David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ruoxuan Xiong & Alex Chin & Sean J. Taylor, 2024. "Data-Driven Switchback Experiments: Theoretical Tradeoffs and Empirical Bayes Designs," Papers 2406.06768, arXiv.org.
- Iavor Bojinov & David Simchi-Levi & Jinglong Zhao, 2023. "Design and Analysis of Switchback Experiments," Management Science, INFORMS, vol. 69(7), pages 3759-3777, July.
- Ali Goli & Anja Lambrecht & Hema Yoganarasimhan, 2024. "A Bias Correction Approach for Interference in Ranking Experiments," Marketing Science, INFORMS, vol. 43(3), pages 590-614, May.
- Ruohan Zhan & Shichao Han & Yuchen Hu & Zhenling Jiang, 2024. "Estimating Treatment Effects under Recommender Interference: A Structured Neural Networks Approach," Papers 2406.14380, arXiv.org, revised Jul 2024.
- Nian Si, 2023. "Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach," Papers 2310.17496, arXiv.org, revised Apr 2024.
- Evan Munro & David Jones & Jennifer Brennan & Roland Nelet & Vahab Mirrokni & Jean Pouget-Abadie, 2023. "Causal Estimation of User Learning in Personalized Systems," Papers 2306.00485, arXiv.org.
- Luofeng Liao & Christian Kroer, 2024. "Statistical Inference and A/B Testing in Fisher Markets and Paced Auctions," Papers 2406.15522, arXiv.org, revised Aug 2024.
- Denis Fougère & Nicolas Jacquemet, 2020.
"Policy Evaluation Using Causal Inference Methods,"
SciencePo Working papers Main
hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," PSE-Ecole d'économie de Paris (Postprint) hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2020. "Policy Evaluation Using Causal Inference Methods," Working Papers hal-03455978, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Post-Print hal-03098058, HAL.
- Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," SciencePo Working papers Main hal-03098058, HAL.
- Fougère, Denis & Jacquemet, Nicolas, 2020. "Policy Evaluation Using Causal Inference Methods," IZA Discussion Papers 12922, Institute of Labor Economics (IZA).
- Zhaonan Qu & Ruoxuan Xiong & Jizhou Liu & Guido Imbens, 2021. "Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference," Papers 2107.12420, arXiv.org, revised Jun 2024.
- Ariel Boyarsky & Hongseok Namkoong & Jean Pouget-Abadie, 2023. "Modeling Interference Using Experiment Roll-out," Papers 2305.10728, arXiv.org, revised Aug 2023.
- Shaina J. Alexandria & Michael G. Hudgens & Allison E. Aiello, 2023. "Assessing intervention effects in a randomized trial within a social network," Biometrics, The International Biometric Society, vol. 79(2), pages 1409-1419, June.
- Vivek F. Farias & Andrew A. Li & Tianyi Peng & Andrew Zheng, 2022. "Markovian Interference in Experiments," Papers 2206.02371, arXiv.org, revised Jun 2022.
- Michael P. Leung, 2022.
"Causal Inference Under Approximate Neighborhood Interference,"
Econometrica, Econometric Society, vol. 90(1), pages 267-293, January.
- Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2021.
- Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
- Davide Viviano & Jess Rudder, 2020. "Policy design in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised May 2024.
- Shan Huang & Chen Wang & Yuan Yuan & Jinglong Zhao & Jingjing Zhang, 2023. "Estimating Effects of Long-Term Treatments," Papers 2308.08152, arXiv.org.
- Elizabeth L. Ogburn & Ilya Shpitser & Youjin Lee, 2020. "Causal inference, social networks and chain graphs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1659-1676, October.
- Hannah Li & Geng Zhao & Ramesh Johari & Gabriel Y. Weintraub, 2021. "Interference, Bias, and Variance in Two-Sided Marketplace Experimentation: Guidance for Platforms," Papers 2104.12222, arXiv.org.
- Steven Wilkins Reeves & Shane Lubold & Arun G. Chandrasekhar & Tyler H. McCormick, 2024. "Model-Based Inference and Experimental Design for Interference Using Partial Network Data," Papers 2406.11940, arXiv.org.
- Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jul 2022.
More about this item
Keywords
statistics: design of experiments; variance minimization; robust optimization; cluster-based randomization; approximation algorithms;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:70:y:2024:i:6:p:4069-4086. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.