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Estimating peer effects in longitudinal dyadic data using instrumental variables

Author

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  • A. James O'Malley
  • Felix Elwert
  • J. Niels Rosenquist
  • Alan M. Zaslavsky
  • Nicholas A. Christakis

Abstract

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Suggested Citation

  • A. James O'Malley & Felix Elwert & J. Niels Rosenquist & Alan M. Zaslavsky & Nicholas A. Christakis, 2014. "Estimating peer effects in longitudinal dyadic data using instrumental variables," Biometrics, The International Biometric Society, vol. 70(3), pages 506-515, September.
    • Handle: RePEc:bla:biomet:v:70:y:2014:i:3:p:506-515
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    File URL: http://hdl.handle.net/10.1111/biom.12172
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    References listed on IDEAS

    as
    1. Bruce Sacerdote, 2001. "Peer Effects with Random Assignment: Results for Dartmouth Roommates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(2), pages 681-704.
    2. Felix Elwert & Nicholas Christakis, 2008. "Wives and ex-wives: A new test for homogamy bias in the widowhood effect," Demography, Springer;Population Association of America (PAA), vol. 45(4), pages 851-873, November.
    3. White, Halbert, 1982. "Instrumental Variables Regression with Independent Observations," Econometrica, Econometric Society, vol. 50(2), pages 483-499, March.
    4. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    5. Cosma Rohilla Shalizi & Andrew C. Thomas, 2011. "Homophily and Contagion Are Generically Confounded in Observational Social Network Studies," Sociological Methods & Research, , vol. 40(2), pages 211-239, May.
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    Citations

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    Cited by:

    1. A. James O'Malley & Thomas A. Bubolz & Jonathan S. Skinner, 2021. "The Diffusion of Health Care Fraud: A Network Analysis," NBER Working Papers 28560, National Bureau of Economic Research, Inc.
    2. Perkins, Jessica M. & Subramanian, S.V. & Christakis, Nicholas A., 2015. "Social networks and health: A systematic review of sociocentric network studies in low- and middle-income countries," Social Science & Medicine, Elsevier, vol. 125(C), pages 60-78.
    3. O'Malley, A. James & Bubolz, Thomas A. & Skinner, Jonathan S., 2023. "The diffusion of health care fraud: A bipartite network analysis," Social Science & Medicine, Elsevier, vol. 327(C).
    4. Onnela, Jukka-Pekka & Landon, Bruce E. & Kahn, Anna-Lea & Ahmed, Danish & Verma, Harish & O'Malley, A. James & Bahl, Sunil & Sutter, Roland W. & Christakis, Nicholas A., 2016. "Polio vaccine hesitancy in the networks and neighborhoods of Malegaon, India," Social Science & Medicine, Elsevier, vol. 153(C), pages 99-106.
    5. Giovanni Abbiati & Jonathan Pratschke, 2021. "‘Like with Like’ or ‘Do Like’? Modelling Peer Effects in The Classroom," CSEF Working Papers 603, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    6. Weihua An & Ying Ding, 2018. "The Landscape of Causal Inference: Perspective From Citation Network Analysis," The American Statistician, Taylor & Francis Journals, vol. 72(3), pages 265-277, July.
    7. Lan Liu & Eric Tchetgen Tchetgen, 2022. "Regression‐based negative control of homophily in dyadic peer effect analysis," Biometrics, The International Biometric Society, vol. 78(2), pages 668-678, June.
    8. Ryohei HAYASHI, 2016. "Peer Effects in Academic Performance," ISER Discussion Paper 0979, Institute of Social and Economic Research, Osaka University.

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