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Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm

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Cited by:

  1. Allassonnière, Stéphanie & Chevallier, Juliette, 2021. "A new class of stochastic EM algorithms. Escaping local maxima and handling intractable sampling," Computational Statistics & Data Analysis, Elsevier, vol. 159(C).
  2. Jiang, Jiming, 2001. "Mixed-effects models with random cluster sizes," Statistics & Probability Letters, Elsevier, vol. 53(2), pages 201-206, June.
  3. Shu Yang & Jae Kwang Kim, 2016. "Likelihood-based Inference with Missing Data Under Missing-at-Random," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 436-454, June.
  4. Steffen Nestler & Edgar Erdfelder, 2023. "Random Effects Multinomial Processing Tree Models: A Maximum Likelihood Approach," Psychometrika, Springer;The Psychometric Society, vol. 88(3), pages 809-829, September.
  5. Varin, Cristiano & Host, Gudmund & Skare, Oivind, 2005. "Pairwise likelihood inference in spatial generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1173-1191, June.
  6. Gonzalez, Jorge & Tuerlinckx, Francis & De Boeck, Paul & Cools, Ronald, 2006. "Numerical integration in logistic-normal models," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1535-1548, December.
  7. Xiaowen Dai & Libin Jin & Lei Shi, 2023. "Quantile regression in random effects meta-analysis model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 469-492, June.
  8. Yang Yang & Ira M. Longini Jr. & M. Elizabeth Halloran & Valerie Obenchain, 2012. "A Hybrid EM and Monte Carlo EM Algorithm and Its Application to Analysis of Transmission of Infectious Diseases," Biometrics, The International Biometric Society, vol. 68(4), pages 1238-1249, December.
  9. Tzougas, George & Yik, Woo Hee & Mustaqeem, Muhammad Waqar, 2019. "Insurance ratemaking using the Exponential-Lognormal regression model," LSE Research Online Documents on Economics 101729, London School of Economics and Political Science, LSE Library.
  10. Yuting Chen & Samis Trevezas & Paul-Henry Cournède, 2015. "A Regularized Particle Filter EM Algorithm Based on Gaussian Randomization with an Application to Plant Growth Modeling," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 847-870, December.
  11. Christian Brinch, 2012. "Efficient simulated maximum likelihood estimation through explicitly parameter dependent importance sampling," Computational Statistics, Springer, vol. 27(1), pages 13-28, March.
  12. Steffen Nestler & Sarah Humberg, 2022. "A Lasso and a Regression Tree Mixed-Effect Model with Random Effects for the Level, the Residual Variance, and the Autocorrelation," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 506-532, June.
  13. Corder Nathan & Yang Shu, 2020. "Estimating Average Treatment Effects Utilizing Fractional Imputation when Confounders are Subject to Missingness," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 249-271, January.
  14. Natarajan, Ranjini & McCulloch, Charles E. & Kiefer, Nicholas M., 2000. "A Monte Carlo EM method for estimating multinomial probit models," Computational Statistics & Data Analysis, Elsevier, vol. 34(1), pages 33-50, July.
  15. Geraci, Marco, 2014. "Linear Quantile Mixed Models: The lqmm Package for Laplace Quantile Regression," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i13).
  16. Rizopoulos, Dimitris, 2012. "Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 491-501.
  17. McLachlan, Geoffrey J. & Krishnan, Thriyambakam & Ng, See Ket, 2004. "The EM Algorithm," Papers 2004,24, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
  18. Meza, Cristian & Jaffrézic, Florence & Foulley, Jean-Louis, 2009. "Estimation in the probit normal model for binary outcomes using the SAEM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1350-1360, February.
  19. Kalyan Das & Angshuman Sarkar, 2014. "Robust inference for generalized partially linear mixed models that account for censored responses and missing covariates -- an application to Arctic data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2418-2436, November.
  20. Cristiano C. Santos & Rosangela H. Loschi, 2017. "Maximum likelihood estimation and parameter interpretation in elliptical mixed logistic regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 26(1), pages 209-230, March.
  21. Klingenberg, Bernhard, 2008. "Regression models for binary time series with gaps," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 4076-4090, April.
  22. Hemant Kulkarni & Jayabrata Biswas & Kiranmoy Das, 2019. "A joint quantile regression model for multiple longitudinal outcomes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(4), pages 453-473, December.
  23. Corder Nathan & Yang Shu, 2020. "Estimating Average Treatment Effects Utilizing Fractional Imputation when Confounders are Subject to Missingness," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 249-271, January.
  24. Isabel Molina & Ewa Strzalkowska‐Kominiak, 2020. "Estimation of proportions in small areas: application to the labour force using the Swiss Census Structural Survey," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 281-310, January.
  25. Ivy Liu & Alan Agresti, 2005. "The analysis of ordered categorical data: An overview and a survey of recent developments," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 1-73, June.
  26. Tzougas, George & Hoon, W. L. & Lim, J. M., 2019. "The negative binomial-inverse Gaussian regression model with an application to insurance ratemaking," LSE Research Online Documents on Economics 101728, London School of Economics and Political Science, LSE Library.
  27. Sik-Yum Lee & Xin-Yuan Song, 2007. "A Unified Maximum Likelihood Approach for Analyzing Structural Equation Models With Missing Nonstandard Data," Sociological Methods & Research, , vol. 35(3), pages 352-381, February.
  28. Yu, Dalei & Zhang, Xinyu & Yau, Kelvin K.W., 2013. "Information based model selection criteria for generalized linear mixed models with unknown variance component parameters," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 245-262.
  29. Tatiyana V. Apanasovich & David Ruppert & Joanne R. Lupton & Natasa Popovic & Nancy D. Turner & Robert S. Chapkin & Raymond J. Carroll, 2008. "Aberrant Crypt Foci and Semiparametric Modeling of Correlated Binary Data," Biometrics, The International Biometric Society, vol. 64(2), pages 490-500, June.
  30. Patricia Dörr & Jan Pablo Burgard, 2019. "Data-driven transformations and survey-weighting for linear mixed models," Research Papers in Economics 2019-16, University of Trier, Department of Economics.
  31. Hai Shu & Bin Nan & Robert Koeppe, 2015. "Multiple testing for neuroimaging via hidden Markov random field," Biometrics, The International Biometric Society, vol. 71(3), pages 741-750, September.
  32. Marcin Hitczenko, 2013. "Modeling anchoring effects in sequential Likert scale questions," Working Papers 13-15, Federal Reserve Bank of Boston.
  33. Jan Pablo Burgard & Patricia Dörr & Ralf Münnich, 2020. "Monte-Carlo Simulation Studies in Survey Statistics – An Appraisal," Research Papers in Economics 2020-04, University of Trier, Department of Economics.
  34. Wang, Jing, 2007. "EM algorithms for nonlinear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3244-3256, March.
  35. Angelo Moretti, 2023. "Estimation of small area proportions under a bivariate logistic mixed model," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3663-3684, August.
  36. Torabi, Mahmoud, 2012. "Likelihood inference in generalized linear mixed models with two components of dispersion using data cloning," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4259-4265.
  37. Pan, Jianxin & Thompson, Robin, 2007. "Quasi-Monte Carlo estimation in generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5765-5775, August.
  38. Jank, Wolfgang, 2006. "Ascent EM for fast and global solutions to finite mixtures: An application to curve-clustering of online auctions," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 747-761, November.
  39. Hamdy F. F. Mahmoud & Inyoung Kim, 2023. "Semiparametric Integrated and Additive Spatio-Temporal Single-Index Models," Mathematics, MDPI, vol. 11(22), pages 1-15, November.
  40. Zhang, Daowen & Davidian, Marie, 2004. "Likelihood and conditional likelihood inference for generalized additive mixed models for clustered data," Journal of Multivariate Analysis, Elsevier, vol. 91(1), pages 90-106, October.
  41. Xu, Liang & Lee, Sik-Yum & Poon, Wai-Yin, 2006. "Deletion measures for generalized linear mixed effects models," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1131-1146, November.
  42. Y. K. Tseng & Y. R. Su & M. Mao & J. L. Wang, 2015. "An extended hazard model with longitudinal covariates," Biometrika, Biometrika Trust, vol. 102(1), pages 135-150.
  43. Wang, Yong, 2010. "Fisher scoring: An interpolation family and its Monte Carlo implementations," Computational Statistics & Data Analysis, Elsevier, vol. 54(7), pages 1744-1755, July.
  44. Kauermann, Goran, 2005. "Penalized spline smoothing in multivariable survival models with varying coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 169-186, April.
  45. Peng Chen & Joshua M. Tebbs & Christopher R. Bilder, 2009. "Group Testing Regression Models with Fixed and Random Effects," Biometrics, The International Biometric Society, vol. 65(4), pages 1270-1278, December.
  46. Hongbin Zhang & Lang Wu, 2019. "An approximate method for generalized linear and nonlinear mixed effects models with a mechanistic nonlinear covariate measurement error model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(4), pages 471-499, May.
  47. An, Xinming & Bentler, Peter M., 2012. "Efficient direct sampling MCEM algorithm for latent variable models with binary responses," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 231-244.
  48. Portier, Francois & Segers, Johan, 2018. "Monte Carlo integration with a growing number of control variates," LIDAM Discussion Papers ISBA 2018001, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  49. Jiaxu Peng & Jungpil Hahn & Ke-Wei Huang, 2023. "Handling Missing Values in Information Systems Research: A Review of Methods and Assumptions," Information Systems Research, INFORMS, vol. 34(1), pages 5-26, March.
  50. Lin, Tsung-I, 2014. "Learning from incomplete data via parameterized t mixture models through eigenvalue decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 183-195.
  51. Qin, Guoyou & Zhu, Zhongyi, 2007. "Robust estimation in generalized semiparametric mixed models for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 98(8), pages 1658-1683, September.
  52. Yehua Li & Annamaria Guolo & F. Owen Hoffman & Raymond J. Carroll, 2007. "Shared Uncertainty in Measurement Error Problems, with Application to Nevada Test Site Fallout Data," Biometrics, The International Biometric Society, vol. 63(4), pages 1226-1236, December.
  53. Dianxu Ren & Roslyn Stone, 2007. "A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1019-1034.
  54. Koutchadé, Philippe & Carpentier, Alain & Féménia, Fabienne, 2015. "Empirical modelling of production decisions of heterogeneous farmers with mixed models," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205098, Agricultural and Applied Economics Association.
  55. Wu, Jianmin & Bentler, Peter M., 2012. "Application of H-likelihood to factor analysis models with binary response data," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 72-79.
  56. Sik-Yum Lee & Xin-Yuan Song, 2004. "Maximum Likelihood Analysis of a General Latent Variable Model with Hierarchically Mixed Data," Biometrics, The International Biometric Society, vol. 60(3), pages 624-636, September.
  57. Elff, Martin & Heisig, Jan Paul & Schaeffer, Merlin & Shikano, Susumu, 2016. "No Need to Turn Bayesian in Multilevel Analysis with Few Clusters: How Frequentist Methods Provide Unbiased Estimates and Accurate Inference," SocArXiv z65s4, Center for Open Science.
  58. Dimitris Rizopoulos & Geert Verbeke & Geert Molenberghs, 2010. "Multiple-Imputation-Based Residuals and Diagnostic Plots for Joint Models of Longitudinal and Survival Outcomes," Biometrics, The International Biometric Society, vol. 66(1), pages 20-29, March.
  59. Koutchade, Philippe & Carpentier, Alain & Femenia, Fabienne, 2015. "Accounting for unobserved heterogeneity in micro-econometric agricultural production models: a random parameter approach," 2015 Conference, August 9-14, 2015, Milan, Italy 212015, International Association of Agricultural Economists.
  60. Ricardo Smith Ramírez, 2007. "FIML estimation of treatment effect models with endogenous selection and multiple censored responses via a Monte Carlo EM Algorithm," Working Papers DTE 403, CIDE, División de Economía.
  61. Baghishani, Hossein & Mohammadzadeh, Mohsen, 2011. "A data cloning algorithm for computing maximum likelihood estimates in spatial generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1748-1759, April.
  62. Li Cai, 2010. "Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis," Journal of Educational and Behavioral Statistics, , vol. 35(3), pages 307-335, June.
  63. Brent A. Coull & David Ruppert & M. P. Wand, 2001. "Simple Incorporation of Interactions into Additive Models," Biometrics, The International Biometric Society, vol. 57(2), pages 539-545, June.
  64. Nagode, M. & Fajdiga, M., 2006. "An alternative perspective on the mixture estimation problem," Reliability Engineering and System Safety, Elsevier, vol. 91(4), pages 388-397.
  65. Tzougas, George & Karlis, Dimitris, 2020. "An EM algorithm for fitting a new class of mixed exponential regression models with varying dispersion," LSE Research Online Documents on Economics 104027, London School of Economics and Political Science, LSE Library.
  66. Heath, Jeffrey W. & Fu, Michael C. & Jank, Wolfgang, 2009. "New global optimization algorithms for model-based clustering," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 3999-4017, October.
  67. Koutchade, Philippe & Carpentier, Alain & Féménia, Fabienne, 2015. "Empirical modeling of production decisions of heterogeneous farmers with random parameter models," Working Papers 210097, Institut National de la recherche Agronomique (INRA), Departement Sciences Sociales, Agriculture et Alimentation, Espace et Environnement (SAE2).
  68. Hongbin Zhang & Lang Wu, 2018. "A non‐linear model for censored and mismeasured time varying covariates in survival models, with applications in human immunodeficiency virus and acquired immune deficiency syndrome studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1437-1450, November.
  69. Tutz, Gerhard & Kauermann, Goran, 2003. "Generalized linear random effects models with varying coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 43(1), pages 13-28, May.
  70. Christian E. Galarza & Luis M. Castro & Francisco Louzada & Victor H. Lachos, 2020. "Quantile regression for nonlinear mixed effects models: a likelihood based perspective," Statistical Papers, Springer, vol. 61(3), pages 1281-1307, June.
  71. Ren, Dianxu & Stone, Roslyn A., 2007. "A Bayesian approach for analyzing a cluster-randomized trial with adjustment for risk misclassification," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5507-5518, August.
  72. Fan, Chunpeng & Zhang, Donghui, 2014. "Wald-type rank tests: A GEE approach," Computational Statistics & Data Analysis, Elsevier, vol. 74(C), pages 1-16.
  73. Jiming Jiang & Thuan Nguyen & J. Sunil Rao, 2015. "The E-MS Algorithm: Model Selection With Incomplete Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1136-1147, September.
  74. Bedair, Khaled & Hong, Yili & Li, Jie & Al-Khalidi, Hussein R., 2016. "Multivariate frailty models for multi-type recurrent event data and its application to cancer prevention trial," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 161-173.
  75. Brent A. Coull & Alan Agresti, 2000. "Random Effects Modeling of Multiple Binomial Responses Using the Multivariate Binomial Logit-Normal Distribution," Biometrics, The International Biometric Society, vol. 56(1), pages 73-80, March.
  76. Celine Marielle Laffont & Marc Vandemeulebroecke & Didier Concordet, 2014. "Multivariate Analysis of Longitudinal Ordinal Data With Mixed Effects Models, With Application to Clinical Outcomes in Osteoarthritis," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 955-966, September.
  77. Emily M. Mitchell & Robert H. Lyles & Amita K. Manatunga & Michelle Danaher & Neil J. Perkins & Enrique F. Schisterman, 2014. "Regression for skewed biomarker outcomes subject to pooling," Biometrics, The International Biometric Society, vol. 70(1), pages 202-211, March.
  78. Liu, Wei & Zhang, Bo & Zhang, Zhiwei & Chen, Baojiang & Zhou, Xiao-Hua, 2015. "A pseudo-likelihood approach for estimating diagnostic accuracy of multiple binary medical tests," Computational Statistics & Data Analysis, Elsevier, vol. 84(C), pages 85-98.
  79. Spark C. Tseung & Ian Weng Chan & Tsz Chai Fung & Andrei L. Badescu & X. Sheldon Lin, 2022. "A Posteriori Risk Classification and Ratemaking with Random Effects in the Mixture-of-Experts Model," Papers 2209.15212, arXiv.org.
  80. Minjeong Jeon & Frank Rijmen & Sophia Rabe-Hesketh, 2017. "A Variational Maximization–Maximization Algorithm for Generalized Linear Mixed Models with Crossed Random Effects," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 693-716, September.
  81. repec:jss:jstsof:19:i02 is not listed on IDEAS
  82. Jo Eidsvik & Sara Martino & Håvard Rue, 2009. "Approximate Bayesian Inference in Spatial Generalized Linear Mixed Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(1), pages 1-22, March.
  83. Thierry Chekouo & Alejandro Murua, 2018. "High-dimensional variable selection with the plaid mixture model for clustering," Computational Statistics, Springer, vol. 33(3), pages 1475-1496, September.
  84. Jan Pablo Burgard & Patricia Dörr, 2018. "Survey-weighted Generalized Linear Mixed Models," Research Papers in Economics 2018-01, University of Trier, Department of Economics.
  85. Yun, Sungcheol & Lee, Youngjo, 2004. "Comparison of hierarchical and marginal likelihood estimators for binary outcomes," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 639-650, April.
  86. Campbell R. Harvey & Yan Liu, 2016. "Rethinking Performance Evaluation," NBER Working Papers 22134, National Bureau of Economic Research, Inc.
  87. Paciorek, Christopher J., 2007. "Bayesian Smoothing with Gaussian Processes Using Fourier Basis Functions in the spectralGP Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 19(i02).
  88. Yang, Miao & Das, Kalyan & Majumdar, Anandamayee, 2016. "Analysis of bivariate zero inflated count data with missing responses," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 73-82.
  89. Tzougas, George & Pignatelli di Cerchiara, Alice, 2021. "The multivariate mixed Negative Binomial regression model with an application to insurance a posteriori ratemaking," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 602-625.
  90. Marco Minozzo & Clarissa Ferrari, 2013. "Multivariate geostatistical mapping of radioactive contamination in the Maddalena Archipelago (Sardinia, Italy): spatial special issue," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(2), pages 195-213, April.
  91. Shanjukta Nath, 2020. "Preference Estimation in Deferred Acceptance with Partial School Rankings," Papers 2010.15960, arXiv.org.
  92. Scott Monroe, 2019. "Estimation of Expected Fisher Information for IRT Models," Journal of Educational and Behavioral Statistics, , vol. 44(4), pages 431-447, August.
  93. Jian Qing Shi & John Copas, 2002. "Publication bias and meta‐analysis for 2×2 tables: an average Markov chain Monte Carlo EM algorithm," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 221-236, May.
  94. Cheng, Jing & Chan, Ngai Hang, 2019. "Efficient inference for nonlinear state space models: An automatic sample size selection rule," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 143-154.
  95. Gonzalez-Manteiga, W. & Lombardia, M.J. & Molina, I. & Morales, D. & Santamaria, L., 2007. "Estimation of the mean squared error of predictors of small area linear parameters under a logistic mixed model," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2720-2733, February.
  96. Thomas Suesse & Ivy Liu, 2013. "Modelling Strategies for Repeated Multiple Response Data," International Statistical Review, International Statistical Institute, vol. 81(2), pages 230-248, August.
  97. Sik-Yum Lee & Jian-Qing Shi, 2001. "Maximum Likelihood Estimation of Two-Level Latent Variable Models with Mixed Continuous and Polytomous Data," Biometrics, The International Biometric Society, vol. 57(3), pages 787-794, September.
  98. Cho, S.-J. & Rabe-Hesketh, S., 2011. "Alternating imputation posterior estimation of models with crossed random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 12-25, January.
  99. Jank, Wolfgang, 2005. "Quasi-Monte Carlo sampling to improve the efficiency of Monte Carlo EM," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 685-701, April.
  100. Popovic, Gordana C. & Hui, Francis K.C. & Warton, David I., 2018. "A general algorithm for covariance modeling of discrete data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 86-100.
  101. Weiping Zhang & Feiyue Xie & Jiaxin Tan, 2020. "A robust joint modeling approach for longitudinal data with informative dropouts," Computational Statistics, Springer, vol. 35(4), pages 1759-1783, December.
  102. Tortora, Cristina & Franczak, Brian C. & Bagnato, Luca & Punzo, Antonio, 2024. "A Laplace-based model with flexible tail behavior," Computational Statistics & Data Analysis, Elsevier, vol. 192(C).
  103. Paciorek, Christopher J., 2007. "Computational techniques for spatial logistic regression with large data sets," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3631-3653, May.
  104. J. E. Mills & C. A. Field & D. J. Dupuis, 2002. "Marginally Specified Generalized Linear Mixed Models: A Robust Approach," Biometrics, The International Biometric Society, vol. 58(4), pages 727-734, December.
  105. Li Cai, 2010. "High-dimensional Exploratory Item Factor Analysis by A Metropolis–Hastings Robbins–Monro Algorithm," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 33-57, March.
  106. Vaida, Florin & Fitzgerald, Anthony P. & DeGruttola, Victor, 2007. "Efficient hybrid EM for linear and nonlinear mixed effects models with censored response," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 5718-5730, August.
  107. Carling, Kenneth & Alam, Moudud, 2007. "Computationally feasible estimation of the covariance structure in Generalized linear mixed models(GLMM)," Working Papers 2007:14, Örebro University, School of Business.
  108. Paul S. Albert & Dean A. Follmann & Shaohua A. Wang & Edward B. Suh, 2002. "A Latent Autoregressive Model for Longitudinal Binary Data Subject to Informative Missingness," Biometrics, The International Biometric Society, vol. 58(3), pages 631-642, September.
  109. Anders Skrondal & Sophia Rabe-Hesketh, 2022. "The Role of Conditional Likelihoods in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 799-834, September.
  110. Liu Yuan & Bottai Matteo, 2009. "Mixed-Effects Models for Conditional Quantiles with Longitudinal Data," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-24, November.
  111. 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.
  112. Sik-Yum Lee & Hong-Tu Zhu, 2002. "Maximum likelihood estimation of nonlinear structural equation models," Psychometrika, Springer;The Psychometric Society, vol. 67(2), pages 189-210, June.
  113. Adhya Sumanta & Banerjee, Tathagata & Chattopadhyay, G., 2007. "Inference on Categorical Survey Response: A Predictive Approach," IIMA Working Papers WP2007-05-07, Indian Institute of Management Ahmedabad, Research and Publication Department.
  114. Marco Minozzo & Clarissa Ferrari, 2011. "Multivariate geostatistical mapping of radioactive contamination in the Maddalena Archipelago (Sardinia, Italy)," Working Papers 21/2011, University of Verona, Department of Economics.
  115. Eickhoff, Jens C. & Zhu, Jun & Amemiya, Yasuo, 2004. "On the simulation size and the convergence of the Monte Carlo EM algorithm via likelihood-based distances," Statistics & Probability Letters, Elsevier, vol. 67(2), pages 161-171, April.
  116. Philip Yu & Paul Lee & W. Wan, 2013. "Factor analysis for paired ranked data with application on parent–child value orientation preference data," Computational Statistics, Springer, vol. 28(5), pages 1915-1945, October.
  117. Kauermann, Goran & Xu, Ronghui & Vaida, Florin, 2008. "Stacked Laplace-EM algorithm for duration models with time-varying and random effects," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2514-2528, January.
  118. Trevezas, S. & Malefaki, S. & Cournède, P.-H., 2014. "Parameter estimation via stochastic variants of the ECM algorithm with applications to plant growth modeling," Computational Statistics & Data Analysis, Elsevier, vol. 78(C), pages 82-99.
  119. Tutz, Gerhard, 2004. "Generalized semiparametrically structured mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 46(4), pages 777-800, July.
  120. Chen, Ming-Hui & Ibrahim, Joseph G. & Shao, Qi-Man, 2009. "Maximum likelihood inference for the Cox regression model with applications to missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 2018-2030, October.
  121. Yang, Ying & Kang, Jian, 2010. "Joint analysis of mixed Poisson and continuous longitudinal data with nonignorable missing values," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 193-207, January.
  122. Tan, Ming & Tian, Guo-Liang & Wang Ng, Kai, 2006. "Hierarchical models for repeated binary data using the IBF sampler," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1272-1286, March.
  123. Maria Marino & Alessio Farcomeni, 2015. "Linear quantile regression models for longitudinal experiments: an overview," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 229-247, August.
  124. Christian N. Brinch, 2008. "Simulated Maximum Likelihood using Tilted Importance Sampling," Discussion Papers 540, Statistics Norway, Research Department.
  125. Booth, James G. & Caffo, Brian S., 2002. "Unequal sampling for Monte Carlo EM algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 39(3), pages 261-270, May.
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