These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
167 related articles for article (PubMed ID: 33094523)
1. A class of generalized linear mixed models adjusted for marginal interpretability. Gory JJ; Craigmile PF; MacEachern SN Stat Med; 2021 Jan; 40(2):427-440. PubMed ID: 33094523 [TBL] [Abstract][Full Text] [Related]
2. Marginally specified generalized linear mixed models: a robust approach. Mills JE; Field CA; Dupuis DJ Biometrics; 2002 Dec; 58(4):727-34. PubMed ID: 12495126 [TBL] [Abstract][Full Text] [Related]
3. Meta-analysis of binary outcomes via generalized linear mixed models: a simulation study. Bakbergenuly I; Kulinskaya E BMC Med Res Methodol; 2018 Jul; 18(1):70. PubMed ID: 29973146 [TBL] [Abstract][Full Text] [Related]
4. Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes. Mikulich-Gilbertson SK; Wagner BD; Grunwald GK; Riggs PD; Zerbe GO Stat Methods Med Res; 2019 May; 28(5):1399-1411. PubMed ID: 29488446 [TBL] [Abstract][Full Text] [Related]
6. Longitudinal Joint Modelling of Ordinal and Overdispersed Count Outcomes: A Bridge Distribution for the Ordinal Random Intercept. Amini P; Moghimbeigi A; Zayeri F; Tapak L; Maroufizadeh S; Verbeke G Comput Math Methods Med; 2021; 2021():5521881. PubMed ID: 33763151 [TBL] [Abstract][Full Text] [Related]
7. Inference in skew generalized t-link models for clustered binary outcome via a parameter-expanded EM algorithm. Tovissodé CF; Diop A; Glèlè Kakaï R PLoS One; 2021; 16(4):e0249604. PubMed ID: 33822818 [TBL] [Abstract][Full Text] [Related]
8. An approximate marginal logistic distribution for the analysis of longitudinal ordinal data. Nooraee N; Abegaz F; Ormel J; Wit E; van den Heuvel ER Biometrics; 2016 Mar; 72(1):253-61. PubMed ID: 26458164 [TBL] [Abstract][Full Text] [Related]
9. Generalized quasi-linear mixed-effects model. Saigusa Y; Eguchi S; Komori O Stat Methods Med Res; 2022 Jul; 31(7):1280-1291. PubMed ID: 35286226 [TBL] [Abstract][Full Text] [Related]
10. Federated learning algorithms for generalized mixed-effects model (GLMM) on horizontally partitioned data from distributed sources. Li W; Tong J; Anjum MM; Mohammed N; Chen Y; Jiang X BMC Med Inform Decis Mak; 2022 Oct; 22(1):269. PubMed ID: 36244993 [TBL] [Abstract][Full Text] [Related]
11. Marginalized binary mixed-effects models with covariate-dependent random effects and likelihood inference. Wang Z; Louis TA Biometrics; 2004 Dec; 60(4):884-91. PubMed ID: 15606408 [TBL] [Abstract][Full Text] [Related]
12. An investigation of penalization and data augmentation to improve convergence of generalized estimating equations for clustered binary outcomes. Geroldinger A; Blagus R; Ogden H; Heinze G BMC Med Res Methodol; 2022 Jun; 22(1):168. PubMed ID: 35681120 [TBL] [Abstract][Full Text] [Related]
13. Laplace approximation, penalized quasi-likelihood, and adaptive Gauss-Hermite quadrature for generalized linear mixed models: towards meta-analysis of binary outcome with sparse data. Ju K; Lin L; Chu H; Cheng LL; Xu C BMC Med Res Methodol; 2020 Jun; 20(1):152. PubMed ID: 32539721 [TBL] [Abstract][Full Text] [Related]
14. Generalized linear mixed models: a practical guide for ecology and evolution. Bolker BM; Brooks ME; Clark CJ; Geange SW; Poulsen JR; Stevens MH; White JS Trends Ecol Evol; 2009 Mar; 24(3):127-35. PubMed ID: 19185386 [TBL] [Abstract][Full Text] [Related]
15. Statistical inference in generalized linear mixed models: a review. Tuerlinckx F; Rijmen F; Verbeke G; De Boeck P Br J Math Stat Psychol; 2006 Nov; 59(Pt 2):225-55. PubMed ID: 17067411 [TBL] [Abstract][Full Text] [Related]
16. Analyzing longitudinal binary data in clinical studies. Li Y; Feng D; Sui Y; Li H; Song Y; Zhan T; Cicconetti G; Jin M; Wang H; Chan I; Wang X Contemp Clin Trials; 2022 Apr; 115():106717. PubMed ID: 35240309 [TBL] [Abstract][Full Text] [Related]
17. Accounting for individual-specific variation in habitat-selection studies: Efficient estimation of mixed-effects models using Bayesian or frequentist computation. Muff S; Signer J; Fieberg J J Anim Ecol; 2020 Jan; 89(1):80-92. PubMed ID: 31454066 [TBL] [Abstract][Full Text] [Related]
18. Using marginal standardisation to estimate relative risk without dichotomising continuous outcomes. Chen Y; Ning Y; Kao SL; Støer NC; Müller-Riemenschneider F; Venkataraman K; Khoo EYH; Tai ES; Tan CS BMC Med Res Methodol; 2019 Jul; 19(1):165. PubMed ID: 31357938 [TBL] [Abstract][Full Text] [Related]
19. SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models. Vock DM; Davidian M; Tsiatis AA J Stat Softw; 2014 Jan; 56():2. PubMed ID: 24688453 [TBL] [Abstract][Full Text] [Related]
20. Random effects and extended generalized partial credit models. Hessen DJ Br J Math Stat Psychol; 2021 May; 74(2):232-256. PubMed ID: 33305365 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]