RJafroc (version 1.0.1)

SsSampleSizeKGivenJ: Number of cases, for specified number of readers, to achieve desired power

Description

Number of cases to achieve the desired power, for specified number of readers J, and specified DBM or OR variance components.

Usage

SsSampleSizeKGivenJ (J, alpha = 0.05, effectSize = 0.05, 
  desiredPower = 0.8, option = "ALL", method = "DBMH", ...)

Arguments

J

The number of readers in the pivotal study

alpha

The significance level of the study, default value is 0.05.

effectSize

The effect size to be used in the study, default value is 0.05.

desiredPower

The desired statistical power, default value is 0.8.

option

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

method

"DBMH" (default) or "ORH".

...

Other necessary parameters, OR or DBM variance components, see details

Value

A list of two elements:

K

The minimum number of cases K in the pivotal study to just achieve the desired statistical power.

power

The predicted statistical power.

Details

Regarding other parameters (...), see details in SsPowerGivenJK. An additional parameter KStar, the number of cases in the pilot study, is required when using OR variability parameters.

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.

Examples

# NOT RUN {
## Following is an example of sample size calculation using the DBM variance 
## components and jackknifing (the default) to
## estimate the variance components
retDbm <- StSignificanceTesting(data = dataset02, 
FOM = "Wilcoxon", method = "DBMH")
effectSize <- retDbm$ciDiffTrtRRRC$Estimate
varCompDBM <- retDbm$varComp
varYTR <- varCompDBM$varComp[3]
varYTC <- varCompDBM$varComp[4]
varYEps <- varCompDBM$varComp[6]
SsSampleSizeKGivenJ(J = 6, varYTR = varYTR, varYTC = varYTC, varYEps = varYEps, 
                 effectSize =effectSize)
                     
## Following is an example of sample size calculation using the OR variance components
retOR <- StSignificanceTesting(data = dataset02, FOM = "Wilcoxon", 
covEstMethod = "Jackknife", method = "ORH")
effectSize <- retOR$ciDiffTrtRRRC$Estimate
varCompOR <- retOR$varComp
varTR <- varCompOR$varCov[2]
cov1 <- varCompOR$varCov[3]
cov2 <- varCompOR$varCov[4]
cov3 <- varCompOR$varCov[5]
varEps <- varCompOR$varCov[6]
KStar <- 114
SsSampleSizeKGivenJ(J = 6, cov1 = cov1, cov2 = cov2, cov3 = cov3, varTR = varTR, varEps= varEps, 
                KStar = KStar, effectSize =effectSize, method = "ORH")

# }
# NOT RUN {
## Following is an example of power calculations using the DBM variance components, 
## and scanning the number of readers
retDbm <- StSignificanceTesting(data = dataset02, 
FOM = "Wilcoxon", method = "DBMH")                     
effectSize <- retDbm$ciDiffTrtRRRC$Estimate
varYTR <- retDbm$varComp$varComp[3]
varYTC <- retDbm$varComp$varComp[4]
varYEps <- retDbm$varComp$varComp[6]
effectSize <- retDbm$ciDiffTrtRRRC$Estimate
for (J in 6:10) {
 ret <- SsSampleSizeKGivenJ(J = J, varYTR = varYTR, varYTC = varYTC, 
 varYEps = varYEps, effectSize =effectSize) 
 message("# of readers = ", J, " estimated # of cases = ", ret$K, ", predicted power = ",
    signif(ret$powerRRRC,3), "\n")
}

## Following is an example of power calculations using the ORH variance components, 
## using bootstrap to estimate variance components
retOR <- StSignificanceTesting(data = dataset02, FOM = "Wilcoxon", 
covEstMethod = "Bootstrap", method = "ORH")
effectSize <- retOR$ciDiffTrtRRRC$Estimate
varCompOR <- retOR$varComp
varTR <- varCompOR$varCov[2]
cov1 <- varCompOR$varCov[3]
cov2 <- varCompOR$varCov[4]
cov3 <- varCompOR$varCov[5]
varEps <- varCompOR$varCov[6]
KStar <- length(dataset02$NL[1,1,,1])
SsSampleSizeKGivenJ(J = 6, cov1 = cov1, cov2 = cov2, cov3 = cov3, 
varTR = varTR, varEps= varEps, 
                 KStar = KStar, effectSize =effectSize, method = "ORH")
# }
# NOT RUN {
# }