Social Network Mediation Analysis: A Latent Space Approach
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DOI: 10.1007/s11336-020-09736-z
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- D. S. Choi & P. J. Wolfe & E. M. Airoldi, 2012. "Stochastic blockmodels with a growing number of classes," Biometrika, Biometrika Trust, vol. 99(2), pages 273-284.
- Qingzhao Yu & Kaelen L. Medeiros & Xiaocheng Wu & Roxanne E. Jensen, 2018. "Nonlinear Predictive Models for Multiple Mediation Analysis: With an Application to Explore Ethnic Disparities in Anxiety and Depression Among Cancer Survivors," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 991-1006, December.
- Hoff P.D. & Raftery A.E. & Handcock M.S., 2002. "Latent Space Approaches to Social Network Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1090-1098, December.
- John Geweke, 1991. "Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments," Staff Report 148, Federal Reserve Bank of Minneapolis.
- Fuhrer, R. & Stansfeld, S. A., 2002. "How gender affects patterns of social relations and their impact on health: a comparison of one or multiple sources of support from "close persons"," Social Science & Medicine, Elsevier, vol. 54(5), pages 811-825, March.
- R. M. Daniel & B. L. De Stavola & S. N. Cousens & S. Vansteelandt, 2015. "Causal mediation analysis with multiple mediators," Biometrics, The International Biometric Society, vol. 71(1), pages 1-14, March.
- Lin Su & Wenbin Lu & Rui Song & Danyang Huang, 2020. "Testing and Estimation of Social Network Dependence With Time to Event Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(530), pages 570-582, April.
- Tracy M. Sweet, 2019. "Modeling Social Networks as Mediators: A Mixed Membership Stochastic Blockmodel for Mediation," Journal of Educational and Behavioral Statistics, , vol. 44(2), pages 210-240, April.
- Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
- Imai, Kosuke & Yamamoto, Teppei, 2013. "Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments," Political Analysis, Cambridge University Press, vol. 21(2), pages 141-171, April.
- Sacha Epskamp & Mijke Rhemtulla & Denny Borsboom, 2017. "Generalized Network Psychometrics: Combining Network and Latent Variable Models," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 904-927, December.
- Daniel K. Sewell & Yuguo Chen, 2015. "Latent Space Models for Dynamic Networks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1646-1657, December.
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- Chiara Di Maria & Antonino Abbruzzo & Gianfranco Lovison, 2022. "Networks as mediating variables: a Bayesian latent space approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 1015-1035, October.
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Keywords
friendship network; mediation analysis; social network analysis; latent space modeling; Bayesian estimation; smoking behavior;All these keywords.
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