Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models. Yue, C., Chen, S., Sair, H. I., Airan, R., & Caffo, B. S. Computational Statistics & Data Analysis, 89:126-133, 2015.
Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models. [link]Link  Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models. [link]Paper  bibtex   
@article{journals/csda/YueCSAC15,
  added-at = {2015-06-24T00:00:00.000+0200},
  author = {Yue, Chen and Chen, Shaojie and Sair, Haris I. and Airan, Raag and Caffo, Brian S.},
  biburl = {https://www.bibsonomy.org/bibtex/2b4e7817bde396462cef64920f659ece7/dblp},
  ee = {http://dx.doi.org/10.1016/j.csda.2015.02.012},
  interhash = {12b2a7b00d774c8ccaf34ae709f13cd4},
  intrahash = {b4e7817bde396462cef64920f659ece7},
  journal = {Computational Statistics & Data Analysis},
  keywords = {dblp},
  pages = {126-133},
  timestamp = {2015-06-25T11:33:14.000+0200},
  title = {Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.},
  url = {http://dblp.uni-trier.de/db/journals/csda/csda89.html#YueCSAC15},
  volume = 89,
  year = 2015
}

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