1126 related articles for article (PubMed ID: 15493516)
1. Assessing convergence of Markov chain Monte Carlo simulations in hierarchical Bayesian models for population pharmacokinetics.
Dodds MG; Vicini P
Ann Biomed Eng; 2004 Sep; 32(9):1300-13. PubMed ID: 15493516
[TBL] [Abstract][Full Text] [Related]
2. Assessing the convergence of Markov Chain Monte Carlo methods: an example from evaluation of diagnostic tests in absence of a gold standard.
Toft N; Innocent GT; Gettinby G; Reid SW
Prev Vet Med; 2007 May; 79(2-4):244-56. PubMed ID: 17292499
[TBL] [Abstract][Full Text] [Related]
3. Well-tempered MCMC simulations for population pharmacokinetic models.
Bois FY; Hsieh NH; Gao W; Chiu WA; Reisfeld B
J Pharmacokinet Pharmacodyn; 2020 Dec; 47(6):543-559. PubMed ID: 32737765
[TBL] [Abstract][Full Text] [Related]
4. Bayesian analysis of population PK/PD models: general concepts and software.
Lunn DJ; Best N; Thomas A; Wakefield J; Spiegelhalter D
J Pharmacokinet Pharmacodyn; 2002 Jun; 29(3):271-307. PubMed ID: 12449499
[TBL] [Abstract][Full Text] [Related]
5. Bayesian hierarchical models for multi-level repeated ordinal data using WinBUGS.
Qiu Z; Song PX; Tan M
J Biopharm Stat; 2002 May; 12(2):121-35. PubMed ID: 12413235
[TBL] [Abstract][Full Text] [Related]
6. A Bayesian approach for PK/PD modeling with PD data below limit of quantification.
Zhou H; Hartford A; Tsai K
J Biopharm Stat; 2012; 22(6):1220-43. PubMed ID: 23075019
[TBL] [Abstract][Full Text] [Related]
7. RWTY (R We There Yet): An R Package for Examining Convergence of Bayesian Phylogenetic Analyses.
Warren DL; Geneva AJ; Lanfear R
Mol Biol Evol; 2017 Apr; 34(4):1016-1020. PubMed ID: 28087773
[TBL] [Abstract][Full Text] [Related]
8. Bayesian hierarchical model for analyzing multiresponse longitudinal pharmacokinetic data.
Zhao L; Xia Z
Stat Med; 2017 Dec; 36(30):4816-4830. PubMed ID: 28960369
[TBL] [Abstract][Full Text] [Related]
9. AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics.
Nylander JA; Wilgenbusch JC; Warren DL; Swofford DL
Bioinformatics; 2008 Feb; 24(4):581-3. PubMed ID: 17766271
[TBL] [Abstract][Full Text] [Related]
10. Input estimation for drug discovery using optimal control and Markov chain Monte Carlo approaches.
Trägårdh M; Chappell MJ; Ahnmark A; Lindén D; Evans ND; Gennemark P
J Pharmacokinet Pharmacodyn; 2016 Apr; 43(2):207-21. PubMed ID: 26932466
[TBL] [Abstract][Full Text] [Related]
11. Performance comparison of first-order conditional estimation with interaction and Bayesian estimation methods for estimating the population parameters and its distribution from data sets with a low number of subjects.
Pradhan S; Song B; Lee J; Chae JW; Kim KI; Back HM; Han N; Kwon KI; Yun HY
BMC Med Res Methodol; 2017 Dec; 17(1):154. PubMed ID: 29191177
[TBL] [Abstract][Full Text] [Related]
12. A gradient Markov chain Monte Carlo algorithm for computing multivariate maximum likelihood estimates and posterior distributions: mixture dose-response assessment.
Li R; Englehardt JD; Li X
Risk Anal; 2012 Feb; 32(2):345-59. PubMed ID: 21906114
[TBL] [Abstract][Full Text] [Related]
13. Markov chain Monte Carlo inference for Markov jump processes via the linear noise approximation.
Stathopoulos V; Girolami MA
Philos Trans A Math Phys Eng Sci; 2013 Feb; 371(1984):20110541. PubMed ID: 23277599
[TBL] [Abstract][Full Text] [Related]
14. VMCMC: a graphical and statistical analysis tool for Markov chain Monte Carlo traces.
Ali RH; Bark M; Miró J; Muhammad SA; Sjöstrand J; Zubair SM; Abbas RM; Arvestad L
BMC Bioinformatics; 2017 Feb; 18(1):97. PubMed ID: 28187712
[TBL] [Abstract][Full Text] [Related]
15. Comparing hierarchical models via the marginalized deviance information criterion.
Quintero A; Lesaffre E
Stat Med; 2018 Jul; 37(16):2440-2454. PubMed ID: 29579777
[TBL] [Abstract][Full Text] [Related]
16. Simultaneous versus sequential pharmacokinetic-pharmacodynamic population analysis using an iterative two-stage Bayesian technique.
Proost JH; Schiere S; Eleveld DJ; Wierda JM
Biopharm Drug Dispos; 2007 Nov; 28(8):455-73. PubMed ID: 17847121
[TBL] [Abstract][Full Text] [Related]
17. How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS.
Lambert PC; Sutton AJ; Burton PR; Abrams KR; Jones DR
Stat Med; 2005 Aug; 24(15):2401-28. PubMed ID: 16015676
[TBL] [Abstract][Full Text] [Related]
18. Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods.
Lele SR; Dennis B; Lutscher F
Ecol Lett; 2007 Jul; 10(7):551-63. PubMed ID: 17542934
[TBL] [Abstract][Full Text] [Related]
19. Combining MCMC with 'sequential' PKPD modelling.
Lunn D; Best N; Spiegelhalter D; Graham G; Neuenschwander B
J Pharmacokinet Pharmacodyn; 2009 Feb; 36(1):19-38. PubMed ID: 19132515
[TBL] [Abstract][Full Text] [Related]
20. Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.
Bustad A; Terziivanov D; Leary R; Port R; Schumitzky A; Jelliffe R
Clin Pharmacokinet; 2006; 45(4):365-83. PubMed ID: 16584284
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]