Have a personal or library account? Click to login
Using Social Network Information for Survey Estimation Cover

Using Social Network Information for Survey Estimation

By: Thomas Suesse and  Ray Chambers  
Open Access
|Mar 2018

References

  1. Butts, C. 2008. “Network: A Package for Managing Relational Data in R.” Journal of Statistical Software 24(2): 1-36. Doi: http://dx.doi.org/10.18637/jss.v024.i06.10.18637/jss.v024.i06
  2. Carrington, P., J. Scott, and S. Wasserman. 2005. Models and Methods in Social Network Analysis. New York: Cambridge University Press.10.1017/CBO9780511811395
  3. Chambers, R., H. Chandra, and N. Tzavidis. 2011. “On Bias-Robust Mean Squared Error Estimation for Pseudo-Linear Small Area Estimators.” Survey Methodology 37: 153-170. Available at: http://www5.statcan.gc.ca/olc-cel/olc.action?ObjId¼12-001-X201100211604&ObjType¼47&lang¼en (accessed September 2017).
  4. Chambers, R.L. and R.G. Clark. 2012. An Introduction to Model-Based Survey Sampling with Applications. Oxford: Oxford University Press.10.1093/acprof:oso/9780198566625.001.0001
  5. Clark, R.G. and R.L. Chambers. 2008. “Adaptive Calibration for Prediction of Finite Population Totals.” Survey Methodology 34: 163-172. Available at: http://www.statcan.gc.ca/pub/12-001-x/2008002/article/10757-eng.pdf (accessed September 2017).
  6. Doreian, P., K. Teuter, and C.H. Wang. 1984. “Network Auto-Correlation Models - some Monte-Carlo Results.” Sociological Methods & Research 13(2): 155-200. Doi: https://doi.org/10.1177/0049124184013002001.10.1177/0049124184013002001
  7. Duke, J.B. 1993. “Estimation of the Network Effects Model in a Large Data Set.” Sociological Methods & Research 21(4): 465-481. Doi: https://doi.org/10.1177/0049124193021004003.10.1177/0049124193021004003
  8. Frank, O. and D. Strauss. 1986. “Markov Graphs.” Journal of the American Statistical Association 81(395): 832-842. Doi: http://dx.doi.org/10.1080/01621459.1986.10478342.10.1080/01621459.1986.10478342
  9. Friedkin, N.E. 1990. “Social Networks in Structural Equation Models.” Social Psychology Quarterly 53(4): 316-328.10.2307/2786737
  10. Goldstein, H. 1989. “Restricted Unbiased Iterative Generalized Least-Squares Estimation.” Biometrika 76(3): 622-623. Doi: https://doi.org/10.1093/biomet/76.3.622.10.1093/biomet/76.3.622
  11. Handcock, M.S., A.E. Raftery, and J.M. Tantrum. 2007. “Model-Based Clustering for Social Networks.” Journal of the Royal Statistical Society Series A 170: 301-322. Doi: http://dx.doi.org/10.1111/j.1467-985X.2007.00471.x.10.1111/j.1467-985X.2007.00471.x
  12. Hunter, D., M. Handcock, C. Butts, S. Goodreau, and M. Morris. 2008b. “ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks.” Journal of Statistical Software 24(2): 1-29. Doi: http://dx.doi.org/10.18637/jss.v024.i03.10.18637/jss.v024.i03274343819756229
  13. Hunter, D.R. 2007. “Curved Exponential Family Models for Social Networks.” Social Networks 29(2): 216-230. Doi: http://dx.doi.org/10.1198/106186006X133069.10.1198/106186006X133069
  14. Hunter, D.R., S.M. Goodreau, and M.S. Handcock. 2008a. “Goodness of Fit of Social Network Models.” Journal of the American Statistical Association 103(481): 248-258. Doi: http://dx.doi.org/10.1198/016214507000000446.10.1198/016214507000000446
  15. Hunter, D.R. and M.S. Handcock. 2006. “Inference in Curved Exponential Family Models for Networks.” Journal of Computational and Graphical Statistics 15(3): 565-583. Doi: http://dx.doi.org/10.1198/106186006X133069.10.1198/106186006X133069
  16. Koskinen, J., G. Robins, and P. Pattison. 2010. “Analysing Exponential Random Graph (p-star) Models with Missing Data Using Bayesian Data Augmentation.” Statistical Methodology 7(3): 366-384. Doi: https://doi.org/10.1016/j.stamet.2009.09.007.10.1016/j.stamet.2009.09.007
  17. Leenders, R. 2002. “Modeling Social Influence Through Network Autocorrelation: Constructing the Weight Matrix.” Social Networks 24(1): 21-47. Doi: https://doi.org/10.1016/S0378-8733(0100049-1).10.1016/S0378-8733(0100049-1)
  18. Marsden, P.V. and N.E. Friedkin. 1993. “Network Studies of Social-Influence.” Sociological Methods & Research 22(1): 127-151. Doi: https://doi.org/10.1177/0049124193022001006.10.1177/0049124193022001006
  19. Ord, K. 1975. “Estimation Methods for Models of Spatial Interaction.” Journal of the American Statistical Association 70(349): 120-126. Doi: http://amstat.tandfonline.com/ https://doi/abs/10.1080/01621459.1975.10480272.10.1080/01621459.1975.10480272
  20. Pattison, P., G. Robins, T. Snijders, and P. Wang. 2013. “Conditional Estimation of Exponential Random Graph Models from Snowball Sampling Designs.” Journal of Mathematical Psychology 57(6): 284-296. Doi: https://doi.org/10.1016/j.jmp.2013.05.004.10.1016/j.jmp.2013.05.004
  21. Royall, R.M. 1976. “Linear Least-Squares Prediction Approach to 2-Stage Sampling.” Journal of the American Statistical Association 71(355): 657-664. Doi: http://dx.doi.org/10.2307/2285596.10.1080/01621459.1976.10481542
  22. Särndal, C., B. Swensson, and J. Wretman. 1992. Model Assisted Survey Sampling. Springer series in statistics. New York: Springer-Verlag.10.1007/978-1-4612-4378-6
  23. Snijders, T. 2002. “Markov Chain Monte Carlo Estimation of Exponential Random Graph Models.” Journal of Social Structure 1-40. Available at: http://citeseerx.ist.psu.edu/viewdoc/download?doi¼10.1.1.20.5323&rep¼rep1&type¼pdf (accessed September 2017).
  24. Snijders, T., P. Pattison, G. Robins, and M. Handcock. 2006. “New Specifications for Exponential Random Graph Models.” Sociological Methodology 36: 99-153. Doi: http://dx.doi.org/10.1111/j.1467-9531.2006.00176.x.10.1111/j.1467-9531.2006.00176.x
  25. Strauss, D. and M. Ikeda. 1990. “Pseudolikelihood Estimation for Social Networks.” Journal of the American Statistical Association 85(409): 204-212. Doi: http://dx.doi.org/10.2307/2289546.10.1080/01621459.1990.10475327
  26. Suesse, T. 2012a. “Estimation in Autoregressive Population Models.” In Proceedings of Fifth Annual ASEARC Research Conference, 11-14. Applied Statistics and Research Collaboration (ASEARC). 2-3 February 2012, Wollongong, Australia. Available at: http://eis.uow.edu.au/asearc/5thAnnResCon/index.html (accessed September 2017).
  27. Suesse, T. 2012b. “Marginalized Exponential Random Graph Models.” Journal of Computational and Graphical Statistics 21(4): 883-900. Doi: http://dx.doi.org/10.1080/10618600.2012.694750.10.1080/10618600.2012.694750
  28. Suesse, T. and R. Chambers. 2012. Using Social Network Information for Survey Estimation. Report 11/12, National Institute of Applied Statistics Research Australia, University of Wollongong. Available at: http://niasra.uow.edu.au/content/groups/public/@web/@inf/@math/documents/doc/uow137689.pdf (accessed September 2017).
  29. Suesse, T. and R. Chambers. 2014. Using Social Network Information for Survey Estimation. Report 13/14, National Institute of Applied Statistics Research Australia, University of Wollongong. Available at: http://niasra.uow.edu.au/content/groups/public/@web/@inf/@math/documents/mm/uow182447.pdf (accessed September 2017).
  30. Suesse, T. and A. Zammit Mangion. 2017. “Computational Aspects of the em Algorithm for Spatial Econometric Models with Missing Data.” Journal of Statistical Computation and Simulation 87: 1767-1786. Doi: http://dx.doi.org/10.1080/00949655.2017.1286495.10.1080/00949655.2017.1286495
  31. Thompson, S. and G. Seber. 1996. Adaptive Sampling. Wiley Series in probability and mathematical statistics. New York: Wiley.
  32. Wasserman, S. and K. Faust. 1994. Social Network Analysis: Methods and Applications. New York: Cambridge University Press.10.1017/CBO9780511815478
Language: English
Page range: 181 - 209
Submitted on: Jul 1, 2015
|
Accepted on: Sep 1, 2017
|
Published on: Mar 1, 2018
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2018 Thomas Suesse, Ray Chambers, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.