IDEAS home Printed from https://ideas.repec.org/e/pec52.html
   My authors  Follow this author

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/

617-253-2659

50 Memorial Drive, Cambridge, Massachusetts 02142
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. Dean Eckles & Brett R. Gordon & Garrett A. Johnson, 2018. "Field studies of psychologically targeted ads face threats to internal validity," The National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(23), pages 5254-5255, June.
  3. 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.
  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. Gonzalo Vazquez-Bare, 2017. "Identification and Estimation of Spillover Effects in Randomized Experiments," Papers 1711.02745, arXiv.org, revised Jul 2020.
    3. Davide Viviano, 2019. "Policy Targeting under Network Interference," Papers 1906.10258, arXiv.org, revised Jun 2020.
    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.
    5. 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.
    6. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2019. "Peer Effects in Networks: a Survey," Working Papers halshs-02440709, HAL.
    7. Bryan S. Graham, 2019. "Network Data," Papers 1912.06346, arXiv.org.
    8. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    9. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    10. 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.
    11. 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 Aug 2020.
    12. Susan Athey & Guido Imbens, 2016. "The State of Applied Econometrics - Causality and Policy Evaluation," Papers 1607.00699, arXiv.org.
    13. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
    14. 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.
    15. 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 Jun 2020.

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. 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. 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.

  3. 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 Jul 2020.
    2. Davide Viviano, 2020. "Experimental Design under Network Interference," Papers 2003.08421, arXiv.org, revised Jun 2020.
    3. Susan Athey & Dean Eckles & Guido W. Imbens, 2015. "Exact P-values for Network Interference," NBER Working Papers 21313, National Bureau of Economic Research, Inc.
    4. 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.
    5. 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.
    6. 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.
    7. Stefan Wager & Kuang Xu, 2019. "Experimenting in Equilibrium," Papers 1903.02124, arXiv.org, revised Jun 2020.
    8. Susan Athey & Guido Imbens, 2016. "The Econometrics of Randomized Experiments," Papers 1607.00698, arXiv.org.
    9. 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.
    10. David Holtz & Ruben Lobel & Inessa Liskovich & Sinan Aral, 2020. "Reducing Interference Bias in Online Marketplace Pricing Experiments," Papers 2004.12489, arXiv.org.
    11. 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.

  4. 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. 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.
    3. 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.
    4. 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.
    5. 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

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Dean Eckles should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.