# viewdata_srsc: Build a table of data in the case of A Single reader and A... In BayesianFROC: FROC Analysis by Bayesian Approaches

## Description

In order to confirm that your dataset is correctly formulated, please view the data via table. my program makes new column of confidence levels which are used in my program. So, it is possible that your order of confidence level and Program's order of confidence level are inverse. This function's result table are the one which are used in program.

## Usage

 `1` ```viewdata_srsc(dataList, summary = TRUE) ```

## Arguments

 `dataList` it should include `f, h, NL, NI, C`. The detail of these dataset, please see the endowed datasets. Note that the maximal number of confidence level, denoted by `C`, are included, however, its each confidence level should not included your data. So, to confirm your false positives and hits are correctly correspondence to confidence levels, user should confirm the orders by the function. `summary` TRUE or FALSE, if true then results are printed, if FALSE this function do nothing.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28``` ```## Not run: # First, we prepare an example FROC data "dataList.Chakra.1" in this package. # Note that this data should be formed as a single reader and a single modality. # If data are multiple readers and multiple modalities, i.e.,MRMC-data, # then another function named viewdataMRMC is available for MRMC-data. dat <- get(data("dataList.Chakra.1")) # Show data named "dat"; viewdata_srsc(dat) #The Reason why the author made this \code{viewdata_srsc} is #the code does not refer your confidence level. #More precisely, my program made the column vector of confidence levels #from the its highest number, #so, it may be occur the interpretaion of code for hits and false alarm #are inverse order compared with your data. ## End(Not run)# dottest ```

BayesianFROC documentation built on Jan. 13, 2021, 5:22 a.m.