RJafroc (version 1.3.2)

SsPowerGivenJK: Statistical power for specified numbers of readers and cases

Description

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

Usage

SsPowerGivenJK(
  dataset,
  ...,
  FOM,
  FPFValue = 0.2,
  J,
  K,
  effectSize = NULL,
  method = "DBMH",
  option = "ALL",
  alpha = 0.05
)

Arguments

dataset

The pilot dataset. If set to NULL then variance components must be supplied.

...

Optional variance components, varYTR, varYTC and varYEps. These are needed if dataset is not supplied.

FOM

The figure of merit

FPFValue

Only needed for LROC data and FOM = "PCL" or "ALROC"; where to evaluate a partial curve based figure of merit. The default is 0.2.

J

The number of readers in the pivotal study.

K

The number of cases in the pivotal study.

effectSize

The effect size to be used in the pivotal study. Default is NULL, which uses the observed effect size in the pilot dataset. Must be supplied if dataset is set to NULL and variance components are supplied.

method

"DBMH" (the default) or "ORH".

option

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

alpha

The significance level, default is 0.05.

Value

The expected statistical power.

Details

The default effectSize uses the observed effect size in the pilot study. A numeric value over-rides the default value. This argument must be supplied if dataset = NULL and variance compenents (the ... arguments) are supplied.

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 {
## the following two should give identical results
SsPowerGivenJK(dataset02, FOM = "Wilcoxon", effectSize = 0.05, J = 6, K = 251, method = "DBMH")
a <- UtilVarComponentsDBM(dataset02, FOM = "Wilcoxon")$varComp
SsPowerGivenJK(dataset = NULL, J = 6, K = 251, effectSize = 0.05, method = "DBMH", 
                    list(varYTR = a$varTR, varYTC = a$varTC, varYEps = a$varErr))
                     
## the following two should give identical results
SsPowerGivenJK(dataset02, FOM = "Wilcoxon", effectSize = 0.05, J = 6, K = 251, method = "ORH")
a <- UtilVarComponentsOR(dataset02, FOM = "Wilcoxon")$varComp
KStar <- length(dataset02$NL[1,1,,1])
SsPowerGivenJK(dataset = NULL, effectSize = 0.05, J = 6, K = 251, method = "ORH", 
   list(KStar = KStar, varTR = a$varTR, cov1 = a$cov1, cov2 = a$cov2, 
   cov3 = a$cov3, varEps = a$var))

# }