St | R Documentation |
Performs DBM or OR significance testing for the dataset.
St(
dataset,
FOM,
method = "OR",
covEstMethod = "jackknife",
analysisOption = "RRRC",
alpha = 0.05,
FPFValue = 0.2,
nBoots = 200,
seed = NULL,
details = 0
)
dataset |
The dataset to be analyzed, see |
FOM |
The figure of merit, see |
method |
The significance testing method to be used: |
covEstMethod |
The covariance matrix estimation method in
|
analysisOption |
Determines which factors are regarded as random and which are fixed:
|
alpha |
The significance level (alpha) of the test of the null hypothesis that all modality effects are zero (default: alpha = 0.05). |
FPFValue |
Only needed for |
nBoots |
The number of bootstraps (defaults to 200), only needed if
|
seed |
For bootstraps the seed of the RNG (default: seed = |
details |
Amount of explanations in output, default is 0 for no explanations and 1 for explanations. |
A list containing the results of the analysis.
details
= 0 should suffice for factorial dataset analysis since
the names of the output lists are self-explanatory. For cross-modality
analysis details
= 1 is suggested to better understand the output.
Dorfman DD, Berbaum KS, Metz CE (1992) ROC characteristic rating analysis: Generalization to the Population of Readers and Patients with the Jackknife method, Invest. Radiol. 27, 723-731.
Obuchowski NA, Rockette HE (1995) Hypothesis Testing of the Diagnostic Accuracy for Multiple Diagnostic Tests: An ANOVA Approach with Dependent Observations, Communications in Statistics: Simulation and Computation 24, 285-308.
Hillis SL (2014) A marginal-mean ANOVA approach for analyzing multireader multicase radiological imaging data, Statistics in medicine 33, 330-360.
Thompson JD, Chakraborty DP, Szczepura K, et al. (2016) Effect of reconstruction methods and x-ray tube current-time product on nodule detection in an anthropomorphic thorax phantom: a crossed-modality JAFROC observer study. Medical Physics. 43(3):1265-1274.
Chakraborty DP (2017) Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples, CRC Press, Boca Raton, FL. https://www.routledge.com/Observer-Performance-Methods-for-Diagnostic-Imaging-Foundations-Modeling/Chakraborty/p/book/9781482214840
result <- St(dataset02,FOM = "Wilcoxon", method = "DBM")
result <- St(dataset02,FOM = "Wilcoxon", method = "OR")
result <- St(datasetX, FOM = "wAFROC", method = "OR", analysisOption = "RRRC")
result <- St(dataset05, FOM = "wAFROC")
result <- St(dataset05, FOM = "HrAuc", method = "DBM")
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