RJafroc (version 1.2.0)

SsPowerGivenJK: Statistical power for specified numbers of readers and cases in an ROC study

Description

Calculate the statistical power for specified numbers of readers J, cases K, analysis method and DBM or OR variances components

Usage

SsPowerGivenJK(dataset, J, K, method = "DBMH", option = "ALL",
  alpha = 0.05, ...)

Arguments

dataset

The pilot ROC dataset to be used to extrapolate to the pivotal study. If missing, then variance components and effectSize must be passed as additional parameters.

J

The number of readers in the pivotal study.

K

The number of cases in the pivotal study.

method

"DBMH" or "ORH".

option

Desired generalization, "RRRC", "FRRC", "RRFC" or "ALL" (the default).

alpha

The significance level, default is 0.05.

...

Other parameters, OR or DBM variance components, passed internally, see details

Value

The expected statistical power.

Details

Other parameters ... are reserved for internal use.

References

Hillis SL, Obuchowski NA, Berbaum KS (2011). Power Estimation for Multireader ROC Methods: An Updated and Unified Approach. Acad Radiol, 18, 129--142.

Hillis SL, Obuchowski NA, Schartz KM, Berbaum KS (2005). A comparison of the Dorfman-Berbaum-Metz and Obuchowski-Rockette methods for receiver operating characteristic (ROC) data. Statistics in Medicine, 24(10), 1579--607.

Chakraborty DP (2017) Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples, CRC Press, Boca Raton, FL. https://www.crcpress.com/Observer-Performance-Methods-for-Diagnostic-Imaging-Foundations-Modeling/Chakraborty/p/book/9781482214840

Examples

# NOT RUN {
## An example of sample size calculation with DBM variance componements
SsPowerGivenJK(dataset02, 6, 251, method = "DBMH")
                     
## An example of sample size calculation with OR variance componements.
SsPowerGivenJK(dataset02, 6, 251, method = "ORH")

# }