Because trials to compare digital and analog mammography rely on complex designs, cost large amounts of money and involve the health of many women, accurate power and sample size calculations are essential. In these trials, radiologists read many films using different sorts of digital machines, and with varying forms of image processes. Measures of the accuracy of detection are the hit rate, and the false alarm rate. Each doctor generates several accuracy scores, one for each condition. These measures are correlated. If one uses an accuracy measure for analog machines as a predictor of accuracy on digital machines, another layer of complexity is added. This experimental design leads to analyzing a General Linear Multivariate Model for repeated measures, both fixed and random predictors, and a full model in every cell. For this design, several sorts of power calculations are proposed. The conditional power can be calculated for a specific set of predictor values. Unconditional power is the expected value of conditional power over all possible stochastic realizations of the random predictors. Quantile power is the conditional power with the noncentrality that corresponds to a realization of the random predictors that occurs with specified probability. The theoretical derivations will lead to easily used software and descriptive examples. These will give radiologists tools for rapid calculation and an interactive, graphical approach to sample size determination.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Academic/Teacher Award (ATA) (K07)
Project #
5K07CA088811-06
Application #
7477208
Study Section
Subcommittee G - Education (NCI)
Program Officer
Silkensen, Shannon M
Project Start
2001-07-01
Project End
2011-02-28
Budget Start
2008-09-01
Budget End
2011-02-28
Support Year
6
Fiscal Year
2008
Total Cost
$135,964
Indirect Cost
Name
University of Colorado Denver
Department
Public Health & Prev Medicine
Type
Schools of Medicine
DUNS #
041096314
City
Aurora
State
CO
Country
United States
Zip Code
80045
Kreidler, Sarah M; Muller, Keith E; Grunwald, Gary K et al. (2013) GLIMMPSE: Online Power Computation for Linear Models with and without a Baseline Covariate. J Stat Softw 54:
Brinton, John T; Barke, Lora D; Freivogel, Mary E et al. (2012) Breast cancer risk assessment in 64,659 women at a single high-volume mammography clinic. Acad Radiol 19:95-9
Ringham, Brandy M; Alonzo, Todd A; Grunwald, Gary K et al. (2010) Estimates of sensitivity and specificity can be biased when reporting the results of the second test in a screening trial conducted in series. BMC Med Res Methodol 10:3
Glueck, D H; Karimpour-Fard, A; Mandel, J et al. (2010) Probabilities for separating sets of order statistics. Statistics (Ber) 44:145-153
Feser, William J; Fingerlin, Tasha E; Strand, Matthew J et al. (2009) CALCULATING AVERAGE POWER FOR THE BENJAMINI-HOCHBERG PROCEDURE. J Stat Theory Appl 8:325-352
O'Donnell, Colin I; Glueck, Charles J; Fingerlin, Tasha E et al. (2009) A likelihood model that accounts for censoring due to fetal loss can accurately test the effects of maternal and fetal genotype on the probability of miscarriage. Hum Hered 67:57-65
Glueck, D H; Muller, K E; Karimpour-Fard, A et al. (2008) Expected Power for the False Discovery Rate with Independence. Commun Stat Theory Methods 37:1855-1866
Glueck, D H; Karimpour-Fard, A; Mandel, J et al. (2008) Fast Computation by Block Permanents of Cumulative Distribution Functions of Order Statistics from Several Populations. Commun Stat Theory Methods 37:2815-2824
Glueck, Deborah H; Lamb, Molly M; Lewin, John M et al. (2007) Two-modality mammography may confer an advantage over either full-field digital mammography or screen-film mammography. Acad Radiol 14:670-6
Regan, Elizabeth; Flannelly, Joanne; Bowler, Russell et al. (2005) Extracellular superoxide dismutase and oxidant damage in osteoarthritis. Arthritis Rheum 52:3479-91

Showing the most recent 10 out of 13 publications