Linked Life Data

9147586

Source:http://linkedlifedata.com/resource/pubmed/id/9147586

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1997-5-12
pubmed:abstractText
We consider the design of single- and multiple-stage dose-response trials in which the probability of response is a logistic function of the dose. Knowledge of the parameters of the logistic at the time of planning the trial is represented by a Gaussian prior distribution. Methods are presented for determining a design that approximately optimizes a measure of the accuracy of estimation averaged over the prior distribution. Changes in design due to uncertainty of parameter values are described as well as the changes in sample size required to produce a specified precision. In multiple-stage trials, the initial stage is planned as if it were the only stage. For succeeding stages, the initial Gaussian prior distribution is updated using outcomes at the previous stages. At each such stage, the design optimizes a chosen criterion averaged over the updated prior distribution. The effectiveness of this methodology is evaluated by comparing the operating characteristics of two-stage designs with those of single-stage designs.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
53
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1-10
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
1997
pubmed:articleTitle
The effect of incomplete knowledge of parameter values on single- and multiple-stage designs for logistic regression.
pubmed:affiliation
Department of Mathematics, University of Houston-Clear Lake, Texas 77058, USA.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S.