RJafroc (version 1.0.1)

PlotEmpiricalOperatingCharacteristics: Plot empirical operating characteristics for specified dataset, treatment and reader

Description

Plot empirical operating characteristics (operating points connected by straight lines) for specified treatments and readers, or if desired, plots only (no operating points) averaged over specified treatments and / or readers

Usage

PlotEmpiricalOperatingCharacteristics(dataset, trts = 1, 
   rdrs = 1, opChType = "ROC")

Arguments

dataset

Dataset to be used for plotting

trts

List or vector: integer indices of modalities to be plotted

rdrs

List or vector: integer indices of readers to be plotted

opChType

Type of operating characteristic to be plotted: "ROC"(the default), "FROC", "AFROC", "wAFROC", "AFROC1", or "wAFROC1"

Value

A ggplot2 object containing the operating characteristic plot(s) and a data frame containing the points defining the operating characteristics are returned. For example, the returned objects for "ROC" operating characteristics are as follows:

Plot

ggplot2 object. For continuous or averaged data, operating characteristics curves are plotted without showing operating points. For binned individual data, both operating points and connecting lines are shown. To avoid clutter, if there are more than 20 operating points, they are not shown

Points

Data frame with four columns: abscissa, ordinate, class (which codes modality and reader) and type, which can be "individual", "continuous" or "average"; "individual" refers to a one modality and one reader.

Details

The trts and rdrs are vectors or lists of integer indices, not the corresponding string IDs. For example, if the string ID of the first reader is "0", the value in rdrs should be 1 not 0. The legend shows the string IDs.

If both of trts and rdrs are vectors, all combinations of treatments and readers are plotted. See Example 1.

If both trts and rdrs are lists, they must have the same length. Only the combination of modality and reader at the same position in their respective lists are plotted. If some elements of the treatments and / or readers lists are vectors, the average operating characteristic over the implied treatments and / or readers are plotted. See Example 2.

Examples

# NOT RUN {
## Example 1
## Plot individual empirical ROC plots for all combinations of modalities
## 1 and 2 and readers 1, 2 and 3. Six operating characteristics are plotted.

ret <- PlotEmpiricalOperatingCharacteristics(dataset = 
dataset02, trts = c(1:2), rdrs = c(1:3))
print(ret$Plot)

## Example 2
## Empirical ROC, FROC, AFROC and wAFROC plots. Each plot consists of
## three parts (see Example 3 for correspondences between indices and string identifiers 
## for modalities and readers):
## (1) plot for the 1st modality (string ID "1") and the 2nd reader (string ID "3") 
## (2) plot for the 2nd modality (string ID "2") AVERAGED over the 2nd and 3rd readers 
##     (string IDs "3" and "4"), and 
## (3) plot AVERAGED over the first two modalities (string IDs "1" and "2") AND over 
## the 1st, 2nd and 3rd readers (string IDs "1", "3" and "4") 

plotT <- list(1, 2, c(1:2))
plotR <- list(2, c(2:3), c(1:3))
ret <- PlotEmpiricalOperatingCharacteristics(dataset = dataset04, trts = plotT, rdrs = plotR)
print(ret$Plot)

ret <- PlotEmpiricalOperatingCharacteristics(dataset = dataset04, trts = plotT, rdrs = plotR,
                  opChType = "FROC")               
print(ret$Plot)

ret <- PlotEmpiricalOperatingCharacteristics(dataset = dataset04, trts = plotT, rdrs = plotR,
                  opChType = "AFROC")
print(ret$Plot)

ret <- PlotEmpiricalOperatingCharacteristics(dataset = dataset04, trts = plotT, rdrs = plotR,
                  opChType = "wAFROC")                  
print(ret$Plot)

##Example 3
## Correspondences between indices and string identifiers for modalities and 
## readers in this dataset. Apparently reader "2" did not complete the study.

str(dataset04)

## List of 8
## $ NL          : num [1:5, 1:4, 1:200, 1:7] -Inf -Inf -Inf -Inf -Inf ...
## $ LL          : num [1:5, 1:4, 1:100, 1:3] 5 4 4 3 5 5 4 2 4 5 ...
## $ lesionNum   : int [1:100] 1 1 1 1 1 1 1 1 1 1 ...
## $ lesionID    : num [1:100, 1:3] 1 1 1 1 1 1 1 1 1 1 ...
## $ lesionWeight: num [1:100, 1:3] 1 1 1 1 1 1 1 1 1 1 ...
## $ dataType    : chr "FROC"
## $ modalityID  : chr [1:5] "1" "2" "3" "4" "5"
## $ readerID    : chr [1:4] "1" "3" "4" "5"

# }