Literature DB >> 23806678

Web-based tools for finding optimal designs in biomedical studies.

Weng Kee Wong1.   

Abstract

Experimental costs are rising and applications of optimal design ideas are increasingly applied in many disciplines. However, the theory for constructing optimal designs can be esoteric and its implementation can be difficult. To help practitioners have easier access to optimal designs and better appreciate design issues, we present a web site at http://optimal-design.biostat.ucla.edu/optimal/ capable of generating different types of tailor-made optimal designs for popular models in the biological sciences. This site also evaluates various efficiencies of a user-specified design and so enables practitioners to appreciate robustness properties of the design before implementation.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Continuous design; Dose response design; Multiple-objective optimal design

Mesh:

Year:  2013        PMID: 23806678      PMCID: PMC3781293          DOI: 10.1016/j.cmpb.2013.05.004

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  10 in total

1.  Minimax D-optimal designs for the logistic model.

Authors:  J King; W K Wong
Journal:  Biometrics       Date:  2000-12       Impact factor: 2.571

2.  Bayesian optimal designs for estimating a set of symmetrical quantiles.

Authors:  W Zhu
Journal:  Stat Med       Date:  2001-01-15       Impact factor: 2.373

3.  Multiple-objective designs in a dose-response experiment.

Authors:  W Zhu; W K Wong
Journal:  J Biopharm Stat       Date:  2000-02       Impact factor: 1.051

4.  Maximin D-optimal designs for longitudinal mixed effects models.

Authors:  Mario J N M Ouwens; Frans E S Tan; Martijn P F Berger
Journal:  Biometrics       Date:  2002-12       Impact factor: 2.571

Review 5.  Competing designs for phase I clinical trials: a review.

Authors:  William F Rosenberger; Linda M Haines
Journal:  Stat Med       Date:  2002-09-30       Impact factor: 2.373

6.  Prediction discrepancies for the evaluation of nonlinear mixed-effects models.

Authors:  France Mentré; Sylvie Escolano
Journal:  J Pharmacokinet Pharmacodyn       Date:  2005-11-13       Impact factor: 2.745

7.  The use of a modified Fedorov exchange algorithm to optimise sampling times for population pharmacokinetic experiments.

Authors:  Kayode Ogungbenro; Gordon Graham; Ivelina Gueorguieva; Leon Aarons
Journal:  Comput Methods Programs Biomed       Date:  2005-08-31       Impact factor: 5.428

8.  Multiple-objective optimal designs.

Authors:  Y C Huang; W K Wong
Journal:  J Biopharm Stat       Date:  1998-11       Impact factor: 1.051

Review 9.  Tutorial in biostatistics. Designing studies for dose response.

Authors:  W K Wong; P A Lachenbruch
Journal:  Stat Med       Date:  1996-02-28       Impact factor: 2.373

10.  Practical considerations for optimal designs in clinical dose finding studies.

Authors:  Frank Bretz; Holger Dette; Jose C Pinheiro
Journal:  Stat Med       Date:  2010-03-30       Impact factor: 2.373

  10 in total

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