Literature DB >> 8678052

Optimizing power in allocating resources to exposure assessment in an epidemiologic study.

B G Armstrong1.   

Abstract

We consider an epidemiologic study with a fixed budget, in which resources may be put into increasing sample size or into improving accuracy of exposure assessments. To maximize study power (efficiency), improving accuracy is preferable if and only if the proportional increase in the square of the validity coefficient is more than the proportional increase in total study costs per subject that is required to achieve it. (The validity coefficient is the correlation between the true exposure and the approximate assessment in the study base.) This is most likely to be so if the cost of exposure measurement remains a small proportion of the overall costs per subject. The design with maximum power will not generally have minimum bias in measure of effect, so that alternative optimality criteria are required if this bias is important.

Mesh:

Year:  1996        PMID: 8678052     DOI: 10.1093/oxfordjournals.aje.a008908

Source DB:  PubMed          Journal:  Am J Epidemiol        ISSN: 0002-9262            Impact factor:   4.897


  5 in total

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Journal:  Occup Environ Med       Date:  2004-05       Impact factor: 4.402

2.  Exposure assessment in cohort studies of childhood asthma.

Authors:  Victoria H Arrandale; Michael Brauer; Jeffrey R Brook; Bert Brunekreef; Diane R Gold; Stephanie J London; J David Miller; Halûk Özkaynak; Nola M Ries; Malcolm R Sears; Frances S Silverman; Tim K Takaro
Journal:  Environ Health Perspect       Date:  2010-11-16       Impact factor: 9.031

3.  Optimizing cost-efficiency in mean exposure assessment--cost functions reconsidered.

Authors:  Svend Erik Mathiassen; Kristian Bolin
Journal:  BMC Med Res Methodol       Date:  2011-05-21       Impact factor: 4.615

4.  Bring More Data!-A Good Advice? Removing Separation in Logistic Regression by Increasing Sample Size.

Authors:  Hana Šinkovec; Angelika Geroldinger; Georg Heinze
Journal:  Int J Environ Res Public Health       Date:  2019-11-22       Impact factor: 3.390

Review 5.  Questionnaires in clinical trials: guidelines for optimal design and administration.

Authors:  Phil Edwards
Journal:  Trials       Date:  2010-01-11       Impact factor: 2.279

  5 in total

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