Nonlinear Mixed Effects Models: Theory

作者: Peter L. Bonate

DOI: 10.1007/978-1-4419-9485-1_7

关键词:

摘要: This chapter introduces the theory behind nonlinear mixed effects models through concept of a structural model or covariate coupled to both fixed and random in manner. Modeling estimation parameters face different sources variability (between-subject, inter-occasion, inter-study, residual within-subject) are discussed, as is modeling nature relationship between dependent variable via linear, power, exponential functions. Model building, identifying significant covariates screening modeling, influence analysis, examination goodness fit scrutiny building data set validation internal external techniques discussed.

参考文章(124)
Karl Brendel, Emmanuelle Comets, Céline Laffont, Christian Laveille, France Mentré, Metrics for External Model Evaluation with an Application to the Population Pharmacokinetics of Gliclazide Pharmaceutical Research. ,vol. 23, pp. 2036- 2049 ,(2006) , 10.1007/S11095-006-9067-5
Patrick J. Marroum, Jogarao Gobburu, The product label: How pharmacokinetics and pharmacodynamics reach the prescriber Clinical Pharmacokinectics. ,vol. 41, pp. 161- 169 ,(2002) , 10.2165/00003088-200241030-00001
Hanna E. Silber, Maria C. Kjellsson, Mats O. Karlsson, The impact of misspecification of residual error or correlation structure on the type I error rate for covariate inclusion Journal of Pharmacokinetics and Pharmacodynamics. ,vol. 36, pp. 81- 99 ,(2009) , 10.1007/S10928-009-9112-1
David H. Salinger, David K. Blough, Paolo Vicini, Claudio Anasetti, Paul V. O'Donnell, Brenda M. Sandmaier, Jeannine S. McCune, A limited sampling schedule to estimate individual pharmacokinetic parameters of fludarabine in hematopoietic cell transplant patients Clinical Cancer Research. ,vol. 15, pp. 5280- 5287 ,(2009) , 10.1158/1078-0432.CCR-09-0427
Stephanie Läer, Jeffrey S. Barrett, Bernd Meibohm, The In Silico Child: Using Simulation to Guide Pediatric Drug Development and Manage Pediatric Pharmacotherapy The Journal of Clinical Pharmacology. ,vol. 49, pp. 889- 904 ,(2009) , 10.1177/0091270009337513
M. P. Wand, Data-Based Choice of Histogram Bin Width The American Statistician. ,vol. 51, pp. 59- 64 ,(1997) , 10.1080/00031305.1997.10473591
Lawrence J. Lesko, Malcolm Rowland, Carl C. Peck, Terrence F. Blaschke, Optimizing the science of drug development: opportunities for better candidate selection and accelerated evaluation in humans. The Journal of Clinical Pharmacology. ,vol. 40, pp. 803- 814 ,(2000) , 10.1177/00912700022009530
D Mould, Population pharmacokinetic and adverse event analysis of topotecan in patients with solid tumors. Clinical Pharmacology & Therapeutics. ,vol. 71, pp. 334- 348 ,(2002) , 10.1067/MCP.2002.123553
MARIE DAVIDIAN, A. RONALD GALLANT, The nonlinear mixed effects model with a smooth random effects density Biometrika. ,vol. 80, pp. 475- 488 ,(1993) , 10.1093/BIOMET/80.3.475
Susan E. Tett, Nicholas H. G. Holford, Andrew J. McLachlan, Population pharmacokinetics and pharmacodynamics : An underutilized resource Drug Information Journal. ,vol. 32, pp. 693- 710 ,(1998) , 10.1177/009286159803200310