Seems that the treatment labels were wrongly inverted in the results of `StSignificanceTesting`?

[huangmozhilv]

Here are my codes:

 library(RJafroc)
 library(flextable)
 library(gtsummary)
 library(readxl)
 library(dplyr)
 library(magrittr)

 frocCr_fp <- file.path('../out/Stage1_frocCr.xlsx')
 x <- DfReadDataFile(frocCr_fp, newExcelFileFormat = TRUE)

 ret_st <- StSignificanceTesting(x, FOM = "AFROC", method = "DBM")
 # ret_fom <- UtilFigureOfMerit(x, FOM = "AFROC") # same as ret_st$FOMs$foms

 ret_plt <- PlotEmpiricalOperatingCharacteristics(dataset = x, opChType = "AFROC")
 ret_plt$Plot

 # export tables to docx
 ReaderID_df <- readxl::read_excel(ID_book_fp, sheet='ReaderID')

 trt_rdr_foms <- ret_st$FOMs$foms
 trt_rdr_foms$trt <- row.names(trt_rdr_foms)
 trt_rdr_foms %<>% dplyr::select(trt, tidyr::everything())
 table1 <- flextable::flextable(trt_rdr_foms)

 ret_st$RRRC$FTests$p[1]
 ciAvgRdrEachTrt <- ret_st$RRRC$ciAvgRdrEachTrt
 ciAvgRdrEachTrt$trt <- row.names(ciAvgRdrEachTrt)
 ciAvgRdrEachTrt %<>% dplyr::select(trt, tidyr::everything())
 table2 <- flextable::flextable(ciAvgRdrEachTrt)

 ciDiffTrt <- ret_st$RRRC$ciDiffTrt
 ciDiffTrt$trt <- row.names(ciDiffTrt)
 ciDiffTrt %<>% dplyr::select(trt, tidyr::everything())
 table3 <- flextable::flextable(ciDiffTrt)

The output tables (1-3) are as below:

My question: In the ModalityID variable, I assigned treatment A to be 0 and treatement B to be 1.

1. In table 1, there are half cells with an value of 0.50000000. We think that this is because at this moment we only have the results of either of the two treatment for each reader. We believe that 0.5 should be those ReaderID-ModalityID pairs with missing values. However, the results in table 1 are totally inverted. For example, the data for rdr0-trt0 is missing, however, it is the AUC for rdr0-trt1 is 0.5.
2. In table 3, it shows that trt1-trt0=0.065662269, which is the inverse number of trt1-trt0 in table 2.

Therefore, my question is: Are the trt1 and trt0 in table 1 and table 2 wrongly inverted?

Looking forward to your reply soon. Thank you very much.

[dpc10ster]

1. Please confirm that you are using the master version of RJafroc, not the CRAN version.
2. Regarding your point #2, from your Table 2, I get trt1-trt0 = -0.06565, which is the same as in Table 3.
3. I did not quite understand your point #2; I do know that missing values are not replace with 0.5. Without your data file I cannot address this issue further.

[dpc10ster]

Chances are you have some readers who provide "empty" datasets, i.e., they do not mark any image; this is discussed in detail in my book; the reader gets credit for not generating any false positives but is penalized for not marking any lesions. The AFROC consists of two points, one at the origin and one at (1,1) leading to AUC = 0.5. It is not like "missing data" in statistics - there is a good reason for expecting AUC = 0.5.

[huangmozhilv]

Thank you so much for the explaination.

[dpc10ster]

You are welcome!

On Nov 18, 2020, at 1:51 AM, ccHuang notifications@github.com wrote:

Thank you so much for the explaination.

— You are receiving this because you modified the open/close state. Reply to this email directly, view it on GitHub https://github.com/dpc10ster/RJafroc/issues/58#issuecomment-729472949, or unsubscribe https://github.com/notifications/unsubscribe-auth/AH4NJRDVM2EMTDIZ6I4HIZLSQNVF5ANCNFSM4TYVPASA.

[dpc10ster]

I set auto-renew off

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