IDEAS home Printed from https://ideas.repec.org/r/oup/biomet/v90y2003i3p533-549.html

Modified profile likelihoods in models with stratum nuisance parameters

Citations

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


Cited by:

  1. N. Sartori, 2003. "A note on likelihood asymptotics in normal linear regression," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(1), pages 187-195, March.
  2. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," Working Papers hal-01073733, HAL.
  3. Cavit Pakel & Neil Shephard & Kevin Sheppard & Robert F. Engle, 2021. "Fitting Vast Dimensional Time-Varying Covariance Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 652-668, July.
  4. Lee, Yoonseok & Phillips, Peter C.B., 2015. "Model selection in the presence of incidental parameters," Journal of Econometrics, Elsevier, vol. 188(2), pages 474-489.
  5. Koen Jochmans, 2018. "Semiparametric Analysis of Network Formation," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(4), pages 705-713, October.
  6. Cavit Pakel & Neil Shephard & Kevin Sheppard, 2009. "Nuisance parameters, composite likelihoods and a panel of GARCH models," OFRC Working Papers Series 2009fe03, Oxford Financial Research Centre.
  7. Geert Dhaene & Koen Jochmans, 2015. "Profile-score adjustments for incidental-parameter problems," Sciences Po publications info:hdl:2441/323dml6suu9, Sciences Po.
  8. Geert Dhaene & Koen Jochmans, 2015. "Split-panel Jackknife Estimation of Fixed-effect Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(3), pages 991-1030.
  9. Dhaene, Geert & Jochmans, Koen, 2016. "Likelihood Inference In An Autoregression With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1178-1215, October.
  10. repec:spo:wpecon:info:hdl:2441/f6h8764enu2lskk9p2m9mgp8l is not listed on IDEAS
  11. repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09ij4j0h0h1 is not listed on IDEAS
  12. repec:spo:wpmain:info:hdl:2441/eu4vqp9ompqllr09j0031f620 is not listed on IDEAS
  13. repec:spo:wpmain:info:hdl:2441/dambferfb7dfprc9m052g20qh is not listed on IDEAS
  14. Schumann, Martin & Severini, Thomas A. & Tripathi, Gautam, 2023. "The role of score and information bias in panel data likelihoods," Journal of Econometrics, Elsevier, vol. 235(2), pages 1215-1238.
  15. Geert Dhaene & Koen Jochmans, 2011. "Profile-score Adjustements for Nonlinearfixed-effect Models," Working Papers hal-01073733, HAL.
  16. Jochmans, Koen & Weidner, Martin, 2024. "Inference On A Distribution From Noisy Draws," Econometric Theory, Cambridge University Press, vol. 40(1), pages 60-97, February.
  17. Giuliana Cortese & Nicola Sartori, 2016. "Integrated likelihoods in parametric survival models for highly clustered censored data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(3), pages 382-404, July.
  18. repec:spo:wpecon:info:hdl:2441/dpido2upv86tqc7td18fd2mna is not listed on IDEAS
  19. Kunz, J.S.; & Staub, K.E.; & Winkelmann, R.;, 2018. "Predicting fixed effects in panel probit models," Health, Econometrics and Data Group (HEDG) Working Papers 18/23, HEDG, c/o Department of Economics, University of York.
  20. Geert Dhaene & Koen Jochmans, 2015. "Profile-score adjustments for incidental-parameter problems," Working Papers hal-03460016, HAL.
  21. Asma Saleh, 2024. "Reduced bias estimation of the log odds ratio," Statistical Papers, Springer, vol. 65(8), pages 5293-5331, October.
  22. Di Caterina, Claudia & Kosmidis, Ioannis, 2019. "Location-adjusted Wald statistics for scalar parameters," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 126-142.
  23. Johannes S. Kunz & Kevin E. Staub & Rainer Winkelmann, 2021. "Predicting individual effects in fixed effects panel probit models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1109-1145, July.
  24. Federico Martellosio & Grant Hillier, 2019. "Adjusted QMLE for the spatial autoregressive parameter," Papers 1909.08141, arXiv.org.
  25. Dhaene, Geert & Jochmans, Koen, 2016. "Likelihood Inference In An Autoregression With Fixed Effects," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1178-1215, October.
  26. Pakel, Cavit, 2019. "Bias reduction in nonlinear and dynamic panels in the presence of cross-section dependence," Journal of Econometrics, Elsevier, vol. 213(2), pages 459-492.
  27. Quentin Clairon & Chloé Pasin & Irene Balelli & Rodolphe Thiébaut & Mélanie Prague, 2024. "Parameter estimation in nonlinear mixed effect models based on ordinary differential equations: an optimal control approach," Computational Statistics, Springer, vol. 39(6), pages 2975-3005, September.
  28. F. Bartolucci & R. Bellio & A. Salvan & N. Sartori, 2016. "Modified Profile Likelihood for Fixed-Effects Panel Data Models," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1271-1289, August.
  29. Gaurav Sharma & Thomas Mathew & Ionut Bebu, 2014. "Combining Multivariate Bioassays: Accurate Inference Using Small Sample Asymptotics," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(1), pages 152-166, March.
  30. Luigi Pace & Alessandra Salvan & Laura Ventura, 2011. "Adjustments of profile likelihood through predictive densities," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(5), pages 923-937, October.
  31. repec:spo:wpmain:info:hdl:2441/dpido2upv86tqc7td18fd2mna is not listed on IDEAS
  32. Yanbo Tang & Nancy Reid, 2020. "Modified likelihood root in high dimensions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(5), pages 1349-1369, December.
  33. Shi, Jianwei & Qin, Guoyou & Zhu, Huichen & Zhu, Zhongyi, 2021. "Communication-efficient distributed M-estimation with missing data," Computational Statistics & Data Analysis, Elsevier, vol. 161(C).
  34. Lee, Woojoo & Shi, Jian Qing & Lee, Youngjo, 2010. "Approximate conditional inference in mixed-effects models with binary data," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 173-184, January.
  35. Xuan Leng & Jiaming Mao & Yutao Sun, 2023. "Debiased Inference for Dynamic Nonlinear Panels with Multi-dimensional Heterogeneities," Papers 2305.03134, arXiv.org, revised Jan 2026.
  36. Stein, Markus Chagas & da Silva, Michel Ferreira & Duczmal, Luiz Henrique, 2014. "Alternatives to the usual likelihood ratio test in mixed linear models," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 184-197.
  37. Ventura, Laura & Sartori, Nicola & Racugno, Walter, 2013. "Objective Bayesian higher-order asymptotics in models with nuisance parameters," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 90-96.
  38. Manuel Arellano & Jinyong Hahn, 2005. "Understanding Bias in Nonlinear Panel Models: Some Recent Developments," Working Papers wp2005_0507, CEMFI.
  39. De Bin, Riccardo, 2016. "On the equivalence between conditional and random-effects likelihoods in exponential families," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 34-38.
  40. Sartori, N. & Severini, T.A. & Marras, E., 2010. "An alternative specification of generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 575-584, February.
  41. Martellosio, Federico & Hillier, Grant, 2020. "Adjusted QMLE for the spatial autoregressive parameter," Journal of Econometrics, Elsevier, vol. 219(2), pages 488-506.
  42. repec:spo:wpmain:info:hdl:2441/f6h8764enu2lskk9p2m9mgp8l is not listed on IDEAS
  43. Ruggero Bellio & Annamaria Guolo, 2016. "Integrated Likelihood Inference in Small Sample Meta-analysis for Continuous Outcomes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 191-201, March.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.