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Double hierarchical generalized linear models (with discussion)

Citations

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Cited by:

  1. Wang, Zhanfeng & Noh, Maengseok & Lee, Youngjo & Shi, Jian Qing, 2021. "A general robust t-process regression model," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
  2. Peter McCullagh, 2008. "Sampling bias and logistic models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 643-677, September.
  3. 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.
  4. Leckie, George, 2014. "runmixregls: A Program to Run the MIXREGLS Mixed-Effects Location Scale Software from within Stata," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(c02).
  5. Lee, Sangin & Pawitan, Yudi & Lee, Youngjo, 2015. "A random-effect model approach for group variable selection," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 147-157.
  6. Sun-Joo Cho & Paul Boeck & Susan Embretson & Sophia Rabe-Hesketh, 2014. "Additive Multilevel Item Structure Models with Random Residuals: Item Modeling for Explanation and Item Generation," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 84-104, January.
  7. 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.
  8. David F. Westneat & Matthew Schofield & Jonathan Wright, 2013. "Editor's choice Parental behavior exhibits among-individual variance, plasticity, and heterogeneous residual variance," Behavioral Ecology, International Society for Behavioral Ecology, vol. 24(3), pages 598-604.
  9. Yudi Pawitan & Youngjo Lee, 2017. "Wallet Game: Probability, Likelihood, and Extended Likelihood," The American Statistician, Taylor & Francis Journals, vol. 71(2), pages 120-122, April.
  10. Kwon, Sunghoon & Oh, Seungyoung & Lee, Youngjo, 2016. "The use of random-effect models for high-dimensional variable selection problems," Computational Statistics & Data Analysis, Elsevier, vol. 103(C), pages 401-412.
  11. I. Gijbels & I. Prosdocimi, 2011. "Smooth estimation of mean and dispersion function in extended generalized additive models with application to Italian induced abortion data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2391-2411, December.
  12. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
  13. Joan del Castillo & Juan-Pablo Ortega, 2011. "Hedging of time discrete auto-regressive stochastic volatility options," Papers 1110.6322, arXiv.org.
  14. Matteo Sebastianelli & Sifiso M. Lukhele & Simona Secomandi & Stacey G. Souza & Bettina Haase & Michaella Moysi & Christos Nikiforou & Alexander Hutfluss & Jacquelyn Mountcastle & Jennifer Balacco & S, 2024. "A genomic basis of vocal rhythm in birds," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  15. Fernanda B. Rizzato & Roseli A. Leandro & Clarice G.B. Demétrio & Geert Molenberghs, 2016. "A Bayesian approach to analyse overdispersed longitudinal count data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(11), pages 2085-2109, August.
  16. Afrânio M.C. Vieira & Roseli A. Leandro & Clarice G.B. Dem�trio & Geert Molenberghs, 2011. "Double generalized linear model for tissue culture proportion data: a Bayesian perspective," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(8), pages 1717-1731, September.
  17. Adam Zbyryt & Jakub W Bubnicki & Dries P J Kuijper & Martin Dehnhard & Marcin Churski & Krzysztof Schmidt & Bob WongHandling editor, 2018. "Do wild ungulates experience higher stress with humans than with large carnivores?," Behavioral Ecology, International Society for Behavioral Ecology, vol. 29(1), pages 19-30.
  18. Jin, Shaobo & Lee, Youngjo, 2024. "Standard error estimates in hierarchical generalized linear models," Computational Statistics & Data Analysis, Elsevier, vol. 189(C).
  19. 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.
  20. Rabindra Nath Das & Jeong-Soo Park, 2012. "Discrepancy in regression estimates between log-normal and gamma: some case studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(1), pages 97-111, March.
  21. 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.
  22. Noh, Maengseok & Lee, Youngjo, 2008. "Hierarchical-likelihood approach for nonlinear mixed-effects models," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3517-3527, March.
  23. Stephen R. Martin & Philippe Rast, 2022. "The Reliability Factor: Modeling Individual Reliability with Multiple Items from a Single Assessment," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1318-1342, December.
  24. George Leckie & Robert French & Chris Charlton & William Browne, 2014. "Modeling Heterogeneous Variance–Covariance Components in Two-Level Models," Journal of Educational and Behavioral Statistics, , vol. 39(5), pages 307-332, October.
  25. Noh, Maengseok & Wu, Lang & Lee, Youngjo, 2012. "Hierarchical likelihood methods for nonlinear and generalized linear mixed models with missing data and measurement errors in covariates," Journal of Multivariate Analysis, Elsevier, vol. 109(C), pages 42-51.
  26. Yanyuan Ma & Marc G. Genton, 2010. "Explicit estimating equations for semiparametric generalized linear latent variable models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(4), pages 475-495, September.
  27. Jun, Seung-Pyo & Lee, Jae-Seong & Lee, Juyeon, 2020. "Method of improving the performance of public-private innovation networks by linking heterogeneous DBs: Prediction using ensemble and PPDM models," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
  28. Rabindra Nath Das & Anis Chandra Mukhopadhyay, 2017. "Correlated random effects regression analysis for a log-normally distributed variable," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(5), pages 897-915, April.
  29. Lee, Sangin & Lee, Youngjo & Pawitan, Yudi, 2018. "Sparse pathway-based prediction models for high-throughput molecular data," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 125-135.
  30. Cheung, Eric C.K. & Ni, Weihong & Oh, Rosy & Woo, Jae-Kyung, 2021. "Bayesian credibility under a bivariate prior on the frequency and the severity of claims," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 274-295.
  31. Rezzy Eko Caraka & Yusra Yusra & Toni Toharudin & Rung-Ching Chen & Mohammad Basyuni & Vilzati Juned & Prana Ugiana Gio & Bens Pardamean, 2021. "Did Noise Pollution Really Improve during COVID-19? Evidence from Taiwan," Sustainability, MDPI, vol. 13(11), pages 1-12, May.
  32. Bohua Yu & Wei Song & Yanqing Lang, 2017. "Spatial Patterns and Driving Forces of Greenhouse Land Change in Shouguang City, China," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
  33. Lee, Woojoo & Lim, Johan & Lee, Youngjo & del Castillo, Joan, 2011. "The hierarchical-likelihood approach to autoregressive stochastic volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 248-260, January.
  34. Lee, Youngjo & Oh, Hee-Seok, 2014. "A new sparse variable selection via random-effect model," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 89-99.
  35. Victor H. Lachos & Celso R.B. Cabral & Carlos A. Abanto-Valle, 2012. "A non-iterative sampling Bayesian method for linear mixed models with normal independent distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(3), pages 531-549, July.
  36. David R. Bickel, 2021. "The sufficiency of the evidence, the relevancy of the evidence, and quantifying both with a single number," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1157-1174, October.
  37. Vlasios Voudouris & Robert Gilchrist & Robert Rigby & John Sedgwick & Dimitrios Stasinopoulos, 2012. "Modelling skewness and kurtosis with the BCPE density in GAMLSS," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1279-1293, November.
  38. Matthew Quick & Nick Revington, 2022. "Exploring the global and local patterns of income segregation in Toronto, Canada: A multilevel multigroup modeling approach," Environment and Planning B, , vol. 49(2), pages 637-653, February.
  39. Jiin Choi & Stewart J. Anderson & Thomas J. Richards & Wesley K. Thompson, 2014. "Prediction of transplant-free survival in idiopathic pulmonary fibrosis patients using joint models for event times and mixed multivariate longitudinal data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(10), pages 2192-2205, October.
  40. Wu, Jianmin & Bentler, Peter M., 2013. "Limited information estimation in binary factor analysis: A review and extension," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 392-403.
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