Literature DB >> 11318192

Two-stage design of quantal response studies.

R R Sitter1, C F Wu.   

Abstract

In a quantal response study, there may be insufficient knowledge of the response relationship for the stimulus (or dose) levels to be chosen properly. Information from such a study can be scanty or even unreliable. A two-stage design is proposed for such studies, which can determine whether and how a follow-up (i.e., second-stage) study should be conducted to select additional stimulus levels to compensate for the scarcity of information in the initial study. These levels are determined by using optimal design theory and are based on the fitted model from the data in the initial study. Its advantages are demonstrated using a fishery study.

Mesh:

Year:  1999        PMID: 11318192     DOI: 10.1111/j.0006-341x.1999.00396.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  2 in total

1.  Finding Bayesian Optimal Designs for Nonlinear Models: A Semidefinite Programming-Based Approach.

Authors:  Belmiro P M Duarte; Weng Kee Wong
Journal:  Int Stat Rev       Date:  2014-10-14       Impact factor: 2.217

2.  Hybrid pooled-unpooled design for cost-efficient measurement of biomarkers.

Authors:  Enrique F Schisterman; Albert Vexler; Sunni L Mumford; Neil J Perkins
Journal:  Stat Med       Date:  2010-02-28       Impact factor: 2.373

  2 in total

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