IDEAS home Printed from https://ideas.repec.org/r/bla/biomet/v59y2003i4p762-769.html
   My bibliography  Save this item

Random Effects Selection in Linear Mixed Models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Colette Mair & Sema Nickbakhsh & Richard Reeve & Jim McMenamin & Arlene Reynolds & Rory N Gunson & Pablo R Murcia & Louise Matthews, 2019. "Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-21, December.
  2. Qian Ren & Sudipto Banerjee, 2013. "Hierarchical Factor Models for Large Spatially Misaligned Data: A Low-Rank Predictive Process Approach," Biometrics, The International Biometric Society, vol. 69(1), pages 19-30, March.
  3. Anasu Rabe & D. K. Shangodoyin & K. Thaga, 2019. "Linear Cholesky Decomposition Of Covariance Matrices In Mixed Models With Correlated Random Effects," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 59-70, December.
  4. Qiwei Li & Elias Mpofu & Cheng Yin & Keith W. Turner, 2019. "Perception of Falls and Confidence in Self-Management of Falls among Older Adults," IJERPH, MDPI, vol. 16(24), pages 1-13, December.
  5. Ollier, Edouard, 2022. "Fast selection of nonlinear mixed effect models using penalized likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
  6. Mingan Yang & Min Wang & Guanghui Dong, 2020. "Bayesian variable selection for mixed effects model with shrinkage prior," Computational Statistics, Springer, vol. 35(1), pages 227-243, March.
  7. Korobilis, Dimitris, 2014. "Data-based priors for vector autoregressions with drifting coefficients," SIRE Discussion Papers 2014-022, Scottish Institute for Research in Economics (SIRE).
  8. Chase N. Joyner & Christopher S. McMahan & Joshua M. Tebbs & Christopher R. Bilder, 2020. "From mixed effects modeling to spike and slab variable selection: A Bayesian regression model for group testing data," Biometrics, The International Biometric Society, vol. 76(3), pages 913-923, September.
  9. Joseph G. Ibrahim & Hongtu Zhu & Ramon I. Garcia & Ruixin Guo, 2011. "Fixed and Random Effects Selection in Mixed Effects Models," Biometrics, The International Biometric Society, vol. 67(2), pages 495-503, June.
  10. Haydar Demirhan & Canan Hamurkaroglu, 2008. "Bayesian estimation of log odds ratios from R × C and 2 × 2 × K contingency tables," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(4), pages 405-424, November.
  11. Dawei Liu & Xihong Lin & Debashis Ghosh, 2007. "Semiparametric Regression of Multidimensional Genetic Pathway Data: Least-Squares Kernel Machines and Linear Mixed Models," Biometrics, The International Biometric Society, vol. 63(4), pages 1079-1088, December.
  12. Hanwen Huang, 2022. "Bayesian multi‐level mixed‐effects model for influenza dynamics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1978-1995, November.
  13. Daniel R. Kowal, 2023. "Subset selection for linear mixed models," Biometrics, The International Biometric Society, vol. 79(3), pages 1853-1867, September.
  14. Benjamin R. Saville & Amy H. Herring, 2009. "Testing Random Effects in the Linear Mixed Model Using Approximate Bayes Factors," Biometrics, The International Biometric Society, vol. 65(2), pages 369-376, June.
  15. Zhen Chen & David B. Dunson, 2005. "Rejoinder to "Comments about Joint Modeling of Cluster Size and Binary and Continuous Subunit-Specific Outcomes"," Biometrics, The International Biometric Society, vol. 61(3), pages 866-867, September.
  16. Demirhan, Haydar, 2013. "Bayesian estimation of order-restricted and unrestricted association models," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 109-126.
  17. Yu, Dalei & Yau, Kelvin K.W., 2012. "Conditional Akaike information criterion for generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 629-644.
  18. Ling Zhou & Huazhen Lin & Xinyuan Song & Yi Li, 2014. "Selection of Latent Variables for Multiple Mixed-outcome Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1064-1082, December.
  19. R. H. Rieger & C. R. Weinberg, 2009. "Testing for violations of the homogeneity needed for conditional logistic regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(10), pages 1147-1157.
  20. Satkartar K. Kinney & David B. Dunson, 2007. "Fixed and Random Effects Selection in Linear and Logistic Models," Biometrics, The International Biometric Society, vol. 63(3), pages 690-698, September.
  21. Wang, Hao, 2010. "Sparse seemingly unrelated regression modelling: Applications in finance and econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2866-2877, November.
  22. Tsai-Hung Fan & Yi-Fu Wang & Yi-Chen Zhang, 2014. "Bayesian model selection in linear mixed effects models with autoregressive(p) errors using mixture priors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1814-1829, August.
  23. Mojtaba Ganjali & Taban Baghfalaki, 2018. "Application of Penalized Mixed Model in Identification of Genes in Yeast Cell-Cycle Gene Expression Data," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 6(2), pages 38-41, April.
  24. Cantoni, Eva & Jacot, Nadège & Ghisletta, Paolo, 2024. "Review and comparison of measures of explained variation and model selection in linear mixed-effects models," Econometrics and Statistics, Elsevier, vol. 29(C), pages 150-168.
  25. Mohammadi, Raziyeh & Kazemi, Iraj, 2022. "A robust linear mixed-effects model for longitudinal data using an innovative multivariate skew-Huber distribution," Journal of Multivariate Analysis, Elsevier, vol. 187(C).
  26. David B. Dunson & Zhen Chen, 2004. "Selecting Factors Predictive of Heterogeneity in Multivariate Event Time Data," Biometrics, The International Biometric Society, vol. 60(2), pages 352-358, June.
  27. Lu, Fei & Xue, Liugen & Cai, Xiong, 2020. "GEE analysis in joint mean-covariance model for longitudinal data," Statistics & Probability Letters, Elsevier, vol. 160(C).
  28. Armagan, Artin & Dunson, David, 2011. "Sparse variational analysis of linear mixed models for large data sets," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1056-1062, August.
  29. Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2010. "Stochastic model specification search for Gaussian and partial non-Gaussian state space models," Journal of Econometrics, Elsevier, vol. 154(1), pages 85-100, January.
  30. Yang, Mingan, 2012. "Bayesian variable selection for logistic mixed model with nonparametric random effects," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2663-2674.
  31. Simona Buscemi & Antonella Plaia, 2020. "Model selection in linear mixed-effect models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 529-575, December.
  32. Imori, Shinpei & Rosen, Dietrich von, 2015. "Covariance components selection in high-dimensional growth curve model with random coefficients," Journal of Multivariate Analysis, Elsevier, vol. 136(C), pages 86-94.
  33. Wagner, Helga & Duller, Christine, 2012. "Bayesian model selection for logistic regression models with random intercept," Computational Statistics & Data Analysis, Elsevier, vol. 56(5), pages 1256-1274.
  34. Bo Cai & David B. Dunson, 2006. "Bayesian Covariance Selection in Generalized Linear Mixed Models," Biometrics, The International Biometric Society, vol. 62(2), pages 446-457, June.
  35. Michelle R. Danaher & Anindya Roy & Zhen Chen & Sunni L. Mumford & Enrique F. Schisterman, 2012. "Minkowski--Weyl Priors for Models With Parameter Constraints: An Analysis of the BioCycle Study," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1395-1409, December.
  36. Lee, Kyeong Eun & Kim, Yongku & Xu, Ronghui, 2014. "Bayesian variable selection under the proportional hazards mixed-effects model," Computational Statistics & Data Analysis, Elsevier, vol. 75(C), pages 53-65.
  37. Rabe Anasu & Shangodoyin D. K. & Thaga K., 2019. "Linear Cholesky Decomposition Of Covariance Matrices In Mixed Models With Correlated Random Effects," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 59-70, December.
  38. Jiehuan Sun & Jose D. Herazo‐Maya & Philip L. Molyneaux & Toby M. Maher & Naftali Kaminski & Hongyu Zhao, 2019. "Regularized Latent Class Model for Joint Analysis of High‐Dimensional Longitudinal Biomarkers and a Time‐to‐Event Outcome," Biometrics, The International Biometric Society, vol. 75(1), pages 69-77, March.
  39. Abhik Ghosh & Magne Thoresen, 2018. "Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(2), pages 179-210, April.
  40. Howard D. Bondell & Arun Krishna & Sujit K. Ghosh, 2010. "Joint Variable Selection for Fixed and Random Effects in Linear Mixed-Effects Models," Biometrics, The International Biometric Society, vol. 66(4), pages 1069-1077, December.
  41. Daniels, M.J. & Pourahmadi, M., 2009. "Modeling covariance matrices via partial autocorrelations," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2352-2363, November.
  42. Jieyi Yi & Niansheng Tang, 2022. "Variational Bayesian Inference in High-Dimensional Linear Mixed Models," Mathematics, MDPI, vol. 10(3), pages 1-19, January.
  43. Mingan Yang, 2020. "Bayesian Mixed Effects Model with Variable Selection," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 10(2), pages 27-29, August.
  44. Xinyu Zhang & Hua Liang & Anna Liu & David Ruppert & Guohua Zou, 2016. "Selection Strategy for Covariance Structure of Random Effects in Linear Mixed-effects Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 275-291, March.
  45. Cumhur Yusuf Demirkale & Dan Nettleton & Tapabrata Maiti, 2010. "Linear Mixed Model Selection for False Discovery Rate Control in Microarray Data Analysis," Biometrics, The International Biometric Society, vol. 66(2), pages 621-629, June.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.