Skip to content
National Cancer Institute National Cancer Institute U.S. National Institutes of Health www.cancer.gov
Division of Cancer Prevention logo
Home Site Map Contact DCP
Programs & Resources

Biometry Research Group

Statistical Software

Partial Testing Design

(Written by Stuart G. Baker)

New Approach (with ROC curves): See Baker SG, Pinsky P. A proposed design and analysis for comparing digital and analog mammography: special ROC methods for cancer screening. JASA. June 2001.

Original Approach: These files are based on the manuscript by Baker SG, Connor RJ, Kessler LG. The partial testing design: a less costly way to test equivalence for sensitivity and specificity. Statistics in Medicine 1998;17:2219-2232.

It runs in Mathematica 2.2 (better for graphics) or 3.0 and requires the files listed below.

Downloads

Download All (ZIP, 6KB)

File name / sizeDescription
ptd.m (M File, 11KB) Sample size calculations (and loads other files)
ptdtime.m (M File, 7KB) Compute optimal interval between screening tests
ptddelta.m (M File, 5KB) Create symbolic delta based on model parameters


To reproduce the calculations in the manuscript, load ptd.m.

To obtain the sample size tradeoff curve, use SampleSizePlot[{pN, pA, deltaN}], where pN and pA are the values of p under the null and alternative hypotheses, respectively, and deltaN is the value of delta under the null hypothesis. In the manuscript pN=pA=.09 and deltaN=-.05.

To obtain the minimum value of m* use SampleSizeLimit [{pN,pA,deltaN},n], where n is symbolic. To reproduce the table of optimal times between screens, type OptimalTimeList[deltasym,parsym,psilist]. To plot delta over time, use PlotDelta[deltasym,parsym,{.1,.5}].

Back to top