IDEAS home Printed from https://ideas.repec.org/r/bla/jorssc/v50y2001i3p325-335.html
   My bibliography  Save this item

On the effect of the number of quadrature points in a logistic random effects model: an example

Citations

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


Cited by:

  1. Alejandra Tapia & Victor Leiva & Maria del Pilar Diaz & Viviana Giampaoli, 2019. "Influence diagnostics in mixed effects logistic regression models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 920-942, September.
  2. Daniel McNeish & Denis Dumas & Dario Torre & Neil Rice, 2022. "Modelling time to maximum competency in medical student progress tests," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2007-2034, October.
  3. Broström, Göran & Holmberg, Henrik, 2011. "Generalized linear models with clustered data: Fixed and random effects models," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3123-3134, December.
  4. Bart Spiessens & Emmanuel Lesaffre & Geert Verbeke & KyungMann Kim, 2002. "Group Sequential Methods for an Ordinal Logistic Random-Effects Model Under Misspecification," Biometrics, The International Biometric Society, vol. 58(3), pages 569-575, September.
  5. 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.
  6. 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.
  7. Anders Skrondal & Jouni Kuha, 2012. "Improved Regression Calibration," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 649-669, October.
  8. 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.
  9. Diaz, Mireya, 2015. "Performance measures of the bivariate random effects model for meta-analyses of diagnostic accuracy," Computational Statistics & Data Analysis, Elsevier, vol. 83(C), pages 82-90.
  10. Liming Xiang & Kelvin K. W. Yau & Yer Van Hui & Andy H. Lee, 2008. "Minimum Hellinger Distance Estimation for k-Component Poisson Mixture with Random Effects," Biometrics, The International Biometric Society, vol. 64(2), pages 508-518, June.
  11. Hammon, Angelina & Zinn, Sabine, 2020. "Multiple imputation of binary multilevel missing not at random data," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 69(3), pages 547-564.
  12. Nasim Vahabi & Anoshirvan Kazemnejad & Somnath Datta, 2018. "A Marginalized Overdispersed Location Scale Model for Clustered Ordinal Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 103-134, December.
  13. Daniel McNeish & Jeffrey R. Harring & Denis Dumas, 2023. "A multilevel structured latent curve model for disaggregating student and school contributions to learning," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 545-575, June.
  14. Altaf H Khan, 2019. "An Application of Sinc Function based Quadrature Method in Statistical Models," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 9(4), pages 91-96, May.
  15. 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.
  16. Dragana M. Pavlović & Bryan R.L. Guillaume & Soroosh Afyouni & Thomas E. Nichols, 2020. "Multi‐subject stochastic blockmodels with mixed effects for adaptive analysis of individual differences in human brain network cluster structure," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 74(3), pages 363-396, August.
  17. Harold Doran, 2023. "A Collection of Numerical Recipes Useful for Building Scalable Psychometric Applications," Journal of Educational and Behavioral Statistics, , vol. 48(1), pages 37-69, February.
  18. repec:jss:jstsof:39:i13 is not listed on IDEAS
  19. Casey Codd & Robert Cudeck, 2014. "Nonlinear Random-Effects Mixture Models for Repeated Measures," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 60-83, January.
  20. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
  21. Angelina Hammon & Sabine Zinn, 2020. "Multiple imputation of binary multilevel missing not at random data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 547-564, June.
  22. 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.
  23. Jianxin Pan & Robin Thompson, 2003. "Gauss-Hermite Quadrature Approximation for Estimation in Generalised Linear Mixed Models," Computational Statistics, Springer, vol. 18(1), pages 57-78, March.
  24. 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.
  25. Vock, David & Davidian, Marie & Tsiatis, Anastasios, 2014. "SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 56(c02).
  26. Komárek, Arnost & Lesaffre, Emmanuel, 2008. "Generalized linear mixed model with a penalized Gaussian mixture as a random effects distribution," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3441-3458, March.
  27. Alonso, A. & Litière, S. & Molenberghs, G., 2008. "A family of tests to detect misspecifications in the random-effects structure of generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4474-4486, May.
  28. Stephen Schilling & R. Bock, 2005. "High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature," Psychometrika, Springer;The Psychometric Society, vol. 70(3), pages 533-555, September.
  29. Sophia Rabe-Hesketh & Anders Skrondal & Andrew Pickles, 2004. "Generalized multilevel structural equation modeling," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 167-190, June.
  30. Özgür Asar & Ozlem Ilk, 2016. "First-order marginalised transition random effects models with probit link function," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 925-942, April.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.