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Dean Eckles

Personal Details

First Name:Dean
Middle Name:
Last Name:Eckles
Suffix:
RePEc Short-ID:pec52
[This author has chosen not to make the email address public]
http://deaneckles.com
Twitter: @deaneckles

Affiliation

Sloan School of Management
Massachusetts Institute of Technology (MIT)

Cambridge, Massachusetts (United States)
http://mitsloan.mit.edu/
RePEc:edi:ssmitus (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Athey, Susan & Eckles, Dean & Imbens, Guido W., 2015. "Exact P-Values for Network Interference," Research Papers 3287, Stanford University, Graduate School of Business.

Articles

  1. Dean Eckles & Maurits Kaptein, 2019. "Bootstrap Thompson Sampling and Sequential Decision Problems in the Behavioral Sciences," SAGE Open, , vol. 9(2), pages 21582440198, June.
  2. Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact p-Values for Network Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 230-240, January.
  3. Dean Eckles & Brett R. Gordon & Garrett A. Johnson, 2018. "Field studies of psychologically targeted ads face threats to internal validity," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(23), pages 5254-5255, June.
  4. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.
  5. 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.
  6. Kaptein, Maurits & Eckles, Dean, 2012. "Heterogeneity in the Effects of Online Persuasion," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 176-188.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Athey, Susan & Eckles, Dean & Imbens, Guido W., 2015. "Exact P-Values for Network Interference," Research Papers 3287, Stanford University, Graduate School of Business.

    Cited by:

    1. Athey, Susan & Luca, Michael, 2018. "Economists (and Economics) in Tech Companies," Research Papers 3735, Stanford University, Graduate School of Business.
    2. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Post-Print hal-03072119, HAL.
    3. Kosuke Imai & Zhichao Jiang, 2020. "Identification and sensitivity analysis of contagion effects in randomized placebo‐controlled trials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1637-1657, October.
    4. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jun 2021.
    5. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jun 2020.
    6. Wooyong Jo & Sarang Sunder & Jeonghye Choi & Minakshi Trivedi, 2020. "Protecting Consumers from Themselves: Assessing Consequences of Usage Restriction Laws on Online Game Usage and Spending," Marketing Science, INFORMS, vol. 39(1), pages 117-133, January.
    7. Caeyers, Bet & Fafchamps, Marcel, 2020. "Exclusion bias and the estimation of peer effects," CEPR Discussion Papers 14386, C.E.P.R. Discussion Papers.
    8. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Jun 2021.
    9. 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.
    10. C. Tort`u & I. Crimaldi & F. Mealli & L. Forastiere, 2020. "Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates," Papers 2003.10525, arXiv.org, revised Jun 2020.
    11. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.
    12. Eric Auerbach & Max Tabord-Meehan, 2021. "The Local Approach to Causal Inference under Network Interference," Papers 2105.03810, arXiv.org, revised May 2021.
    13. Bryan S. Graham, 2019. "Network Data," Papers 1912.06346, arXiv.org.
    14. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    15. Dalia Ghanem & Sarojini Hirshleifer & Karen Ortiz-Becerra, 2019. "Testing for Attrition Bias in Field Experiments," Working Papers 202010, University of California at Riverside, Department of Economics, revised Mar 2020.
    16. 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.
    17. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    18. Silvia Noirjean & Marco Mariani & Alessandra Mattei & Fabrizia Mealli, 2020. "Exploiting network information to disentangle spillover effects in a field experiment on teens' museum attendance," Papers 2011.11023, arXiv.org.
    19. Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2020.
    20. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    21. Ramesh Johari & Hannah Li & Inessa Liskovich & Gabriel Weintraub, 2020. "Experimental Design in Two-Sided Platforms: An Analysis of Bias," Papers 2002.05670, arXiv.org, revised Jan 2021.
    22. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    23. 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.
    24. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
    25. Toru Kitagawa & Guanyi Wang, 2020. "Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network," Papers 2012.04055, arXiv.org, revised Jul 2021.
    26. Arun Advani & Bansi Malde, 2018. "Methods to identify linear network models: a review," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-16, December.
    27. Michael P. Leung, 2020. "Treatment and Spillover Effects Under Network Interference," The Review of Economics and Statistics, MIT Press, vol. 102(2), pages 368-380, May.
    28. Bryan S. Graham, 2019. "Network Data," CeMMAP working papers CWP71/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    29. Fredrik Savje, 2021. "Causal inference with misspecified exposure mappings," Papers 2103.06471, arXiv.org.
    30. Giulio Grossi & Patrizia Lattarulo & Marco Mariani & Alessandra Mattei & Ozge Oner, 2020. "Synthetic Control Group Methods in the Presence of Interference: The Direct and Spillover Effects of Light Rail on Neighborhood Retail Activity," Papers 2004.05027, arXiv.org, revised Feb 2021.

Articles

  1. Susan Athey & Dean Eckles & Guido W. Imbens, 2018. "Exact p-Values for Network Interference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 230-240, January.
    See citations under working paper version above.
  2. Dean Eckles & Brett R. Gordon & Garrett A. Johnson, 2018. "Field studies of psychologically targeted ads face threats to internal validity," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(23), pages 5254-5255, June.

    Cited by:

    1. Christina Uhl & Nadia Abou Nabout & Klaus Miller, 2020. "How Much Ad Viewability is Enough? The Effect of Display Ad Viewability on Advertising Effectiveness," Papers 2008.12132, arXiv.org.
    2. Orazi, Davide C. & Johnston, Allen C., 2020. "Running field experiments using Facebook split test," Journal of Business Research, Elsevier, vol. 118(C), pages 189-198.

  3. Jason J Jones & Robert M Bond & Eytan Bakshy & Dean Eckles & James H Fowler, 2017. "Social influence and political mobilization: Further evidence from a randomized experiment in the 2012 U.S. presidential election," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-9, April.

    Cited by:

    1. Cristian Vaccari & Augusto Valeriani, 2018. "Digital Political Talk and Political Participation: Comparing Established and Third Wave Democracies," SAGE Open, , vol. 8(2), pages 21582440187, June.
    2. Davide Viviano, 2020. "Policy choice in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Jun 2021.
    3. Adiyana Sharag-Eldin & Xinyue Ye & Brian Spitzberg & Ming-Hsiang Tsou, 2019. "The role of space and place in social media communication: two case studies of policy perspectives," Journal of Computational Social Science, Springer, vol. 2(2), pages 221-244, July.
    4. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Jun 2021.
    5. Shan Huang & Sinan Aral & Yu Jeffrey Hu & Erik Brynjolfsson, 2020. "Social Advertising Effectiveness Across Products: A Large-Scale Field Experiment," Marketing Science, INFORMS, vol. 39(6), pages 1142-1165, November.
    6. Ekaterina Zhuravskaya & Maria Petrova & Ruben Enikolopov, 2020. "Political Effects of the Internet and Social Media," Post-Print halshs-02491741, HAL.

  4. 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.

    Cited by:

    1. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jun 2021.
    2. Denis Fougère & Nicolas Jacquemet, 2021. "Policy Evaluation Using Causal Inference Methods," Post-Print hal-03098058, HAL.
    3. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jun 2020.
    4. Davide Viviano, 2020. "Policy choice in experiments with unknown interference," Papers 2011.08174, arXiv.org, revised Jun 2021.
    5. Susan Athey & Dean Eckles & Guido W. Imbens, 2015. "Exact P-values for Network Interference," NBER Working Papers 21313, National Bureau of Economic Research, Inc.
    6. C. Tort`u & I. Crimaldi & F. Mealli & L. Forastiere, 2020. "Modelling Network Interference with Multi-valued Treatments: the Causal Effect of Immigration Policy on Crime Rates," Papers 2003.10525, arXiv.org, revised Jun 2020.
    7. Karlsson, Maria & Lundin, Mathias, 2016. "On statistical methods for labor market evaluation under interference between units," Working Paper Series 2016:24, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    8. Sofrygin Oleg & van der Laan Mark J., 2017. "Semi-Parametric Estimation and Inference for the Mean Outcome of the Single Time-Point Intervention in a Causally Connected Population," Journal of Causal Inference, De Gruyter, vol. 5(1), pages 1-35, March.
    9. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    10. Yuchen Hu & Shuangning Li & Stefan Wager, 2021. "Average Treatment Effects in the Presence of Interference," Papers 2104.03802, arXiv.org, revised Apr 2021.
    11. 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.
    12. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    13. Michael P. Leung, 2019. "Causal Inference Under Approximate Neighborhood Interference," Papers 1911.07085, arXiv.org, revised Nov 2020.
    14. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
    15. Miguel Godinho de Matos & Pedro Ferreira & Rodrigo Belo, 2018. "Target the Ego or Target the Group: Evidence from a Randomized Experiment in Proactive Churn Management," Marketing Science, INFORMS, vol. 37(5), pages 793-811, September.
    16. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
    17. Guillaume W Basse & Edoardo M Airoldi, 2018. "Model-assisted design of experiments in the presence of network-correlated outcomes," Biometrika, Biometrika Trust, vol. 105(4), pages 849-858.
    18. David Holtz & Sinan Aral, 2020. "Limiting Bias from Test-Control Interference in Online Marketplace Experiments," Papers 2004.12162, arXiv.org.
    19. Fredrik Savje, 2021. "Causal inference with misspecified exposure mappings," Papers 2103.06471, arXiv.org.

  5. Kaptein, Maurits & Eckles, Dean, 2012. "Heterogeneity in the Effects of Online Persuasion," Journal of Interactive Marketing, Elsevier, vol. 26(3), pages 176-188.

    Cited by:

    1. Blazevic, Vera & Wiertz, Caroline & Cotte, June & de Ruyter, Ko & Keeling, Debbie Isobel, 2014. "GOSIP in Cyberspace: Conceptualization and Scale Development for General Online Social Interaction Propensity," Journal of Interactive Marketing, Elsevier, vol. 28(2), pages 87-100.
    2. Meents, Selmar & Verhagen, Tibert & Merikivi, Jani & Weltevreden, Jesse, 2020. "Persuasive location-based messaging to increase store visits: An exploratory study of fashion shoppers," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    3. Dean Eckles & Maurits Kaptein, 2019. "Bootstrap Thompson Sampling and Sequential Decision Problems in the Behavioral Sciences," SAGE Open, , vol. 9(2), pages 21582440198, June.
    4. Díaz, Estrella & Martín-Consuegra, David, 2016. "A latent class segmentation analysis of airlines based on website evaluation," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 20-40.
    5. Maurits Kaptein & Robin van Emden & Davide Iannuzzi, 2017. "Uncovering noisy social signals: Using optimization methods from experimental physics to study social phenomena," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-14, March.
    6. Estrella Díaz & David Martín-Consuegra & Hooman Estelami, 2016. "A persuasive-based latent class segmentation analysis of luxury brand websites," Electronic Commerce Research, Springer, vol. 16(3), pages 401-424, September.
    7. Pappas, Ilias O. & Kourouthanassis, Panos E. & Giannakos, Michail N. & Chrissikopoulos, Vassilios, 2016. "Explaining online shopping behavior with fsQCA: The role of cognitive and affective perceptions," Journal of Business Research, Elsevier, vol. 69(2), pages 794-803.
    8. Barnes, Stuart J. & Pressey, Andrew D., 2016. "Cyber-mavens and online flow experiences: Evidence from virtual worlds," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 285-296.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-EXP: Experimental Economics (3) 2015-07-11 2015-09-05 2016-10-09. Author is listed
  2. NEP-NET: Network Economics (3) 2015-07-11 2015-09-05 2016-10-09. Author is listed
  3. NEP-ECM: Econometrics (1) 2015-07-11. Author is listed

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