Go to USC home page USC Logo Department of Statistics

Latent variable and mixed effects models

[latent variable and measurement error models, group testing, robustness, Bayesian hierarchical models, generalized linear mixed models, non-linear mixed models, clustering, inter-rater agreement.]

Theme leader: Joshua Tebbs
Theme members: Edwards, Grego, Habing, Hanson, Hitchcock, Lin, Huang, Tebbs, L.Wang

Some publications

  • Bilder, C., Tebbs, J., and Chen, P. (2010). Informative retesting. Journal of the American Statistical Association, 105, 942-955.
  • Huang, X. (2011) Detecting random-effects model misspecification via coarsened data. Computational Statistics and Data Analysis 55 , 703.714.
  • Huang, X. and Tebbs, J. (2009). On latent-variable model misspeci cation in structural measurement error models for binary response. Biometrics, 65, 710-718.
  • Nelson, Kerrie and Edwards, Don (2010). .Improving the reliablity of diagnostic tests in population-based agreement studies. Statistics in Medicine. 29(6), 617-626
  • Huang, Xianzheng; Stefanski, Leonard A.; Davidian, Marie Latent-model robustness in structural measurement error models. Biometrika 93 (2006), no. 1, 53--64.
  • Carolan, Christopher A.; Tebbs, Joshua M. Nonparametric tests for and against likelihood ratio ordering in the two-sample problem. Biometrika 92 (2005), no. 1, 159--171.
  • Hitchcock, D. B. and Chen, Z. (2008), Smoothing Dissimilarities to Cluster Binary Data, Computational Statistics and Data Analysis, 52, 4699-4711.
  • Nelson, Kerrie, and Edwards, Don (2008). On population-based measures of agreement . The Canadian Journal of Statistics, 36: 411-426.
  • Tebbs, Joshua M.; McCann, Melinda H. Large-sample hypothesis tests for stratified group-testing data. J. Agric. Biol. Environ. Stat. 12 (2007), no. 4, 534--551.
  • Tebbs, Joshua M.; Bilder, Christopher R. Hypothesis tests for and against a simple order among proportions estimated by pooled testing. Biom. J. 48 (2006), no. 5, 792--804.
    Return the Statistics Home Page