Abstract
We developed a Bayesian approach to sample size calculations for cross-sectional studies designed to estimate sensitivity and specificity of one or more diagnostic tests. Sample size calculations can be made for common study designs such as one test in one population, two conditionally independent or dependent tests in ≤ 2 populations, and three tests in ≤ 2 populations.We determine a sample size combination that yields high predictive probability, with respect to the future study data, of accurate and precise estimates of sensitivity and specificity. We also consider hypothesis testing for demonstrating the superiority or equivalence of one diagnostic test relative to another. The predictive probability can also be computed when the sample size combination is fixed in advance, thereby providing a "power-like" measure for the future study. The method is straightforward to implement using the S-Plus/R library emBedBUGS together with WinBUGS.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 112-127 |
| Number of pages | 16 |
| Journal | Journal of Agricultural, Biological, and Environmental Statistics |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 1 2007 |
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Keywords
- Bayesian modeling
- Prediction
- Screening tests
- Sensitivity
- Specificity
- WinBUGS
ASJC Scopus subject areas
- Statistics and Probability
- Environmental Science(all)
- Agricultural and Biological Sciences (miscellaneous)
- Agricultural and Biological Sciences(all)
- Statistics, Probability and Uncertainty
- Applied Mathematics
Cite this
Sample size calculations for studies designed to evaluate diagnostic test accuracy. / Branscum, Adam J.; Johnson, Wesley O.; Gardner, Ian.
In: Journal of Agricultural, Biological, and Environmental Statistics, Vol. 12, No. 1, 01.03.2007, p. 112-127.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Sample size calculations for studies designed to evaluate diagnostic test accuracy
AU - Branscum, Adam J.
AU - Johnson, Wesley O.
AU - Gardner, Ian
PY - 2007/3/1
Y1 - 2007/3/1
N2 - We developed a Bayesian approach to sample size calculations for cross-sectional studies designed to estimate sensitivity and specificity of one or more diagnostic tests. Sample size calculations can be made for common study designs such as one test in one population, two conditionally independent or dependent tests in ≤ 2 populations, and three tests in ≤ 2 populations.We determine a sample size combination that yields high predictive probability, with respect to the future study data, of accurate and precise estimates of sensitivity and specificity. We also consider hypothesis testing for demonstrating the superiority or equivalence of one diagnostic test relative to another. The predictive probability can also be computed when the sample size combination is fixed in advance, thereby providing a "power-like" measure for the future study. The method is straightforward to implement using the S-Plus/R library emBedBUGS together with WinBUGS.
AB - We developed a Bayesian approach to sample size calculations for cross-sectional studies designed to estimate sensitivity and specificity of one or more diagnostic tests. Sample size calculations can be made for common study designs such as one test in one population, two conditionally independent or dependent tests in ≤ 2 populations, and three tests in ≤ 2 populations.We determine a sample size combination that yields high predictive probability, with respect to the future study data, of accurate and precise estimates of sensitivity and specificity. We also consider hypothesis testing for demonstrating the superiority or equivalence of one diagnostic test relative to another. The predictive probability can also be computed when the sample size combination is fixed in advance, thereby providing a "power-like" measure for the future study. The method is straightforward to implement using the S-Plus/R library emBedBUGS together with WinBUGS.
KW - Bayesian modeling
KW - Prediction
KW - Screening tests
KW - Sensitivity
KW - Specificity
KW - WinBUGS
UR - http://www.scopus.com/inward/record.url?scp=33947701496&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33947701496&partnerID=8YFLogxK
U2 - 10.1198/108571107X177519
DO - 10.1198/108571107X177519
M3 - Article
AN - SCOPUS:33947701496
VL - 12
SP - 112
EP - 127
JO - Journal of Agricultural, Biological, and Environmental Statistics
JF - Journal of Agricultural, Biological, and Environmental Statistics
SN - 1085-7117
IS - 1
ER -