data_of_36_readers_and_a_single_modality: 36 readers and a sinle modality data

Description Details Author(s) References See Also Examples

Description

An example data-set whose sample size is large.

Details

Frequentist methods fails when a sample size is large. Namely, p value monotonically decreases when the sample size tends to large.

On the other hands, in Bayesian methods, the large samples such as large readers in FROC context fails the MCMC algorithm. Thus Bayesian methods is also not free from such large sample problem in this sense.

This dataset is made for validation that wheter Bayes factor well work which is a subset of data dataList.Chakra.Web.orderd

the number of modalities, denoted by M which is now

1 modality

the number of Confidences, denoted by C which is now

5 Confidence levels

the number of readers, denoted by Q which is now

36 readers

Contents of data_of_36_readers_and_a_single_modality

NL = 142 (Number of Lesions)

NI = 57 (Number of Images)#'

Contents:

Multiple readers and multiple modalities case, i.e., MRMC case

ModalityID ReaderID Confidence levels No. of false alarms No. of hits.
m q c f h
-------------- ------------- ------------------------ ------------------- ----------------
1 1 5 0 12
1 1 4 3 22
1 1 3 7 18
1 1 2 12 18
1 1 1 8 15
1 2 5 0 14
1 2 4 4 24
1 2 3 9 17
1 2 2 14 15
1 2 1 10 6
1 3 5 0 26
1 3 4 3 39
1 3 3 6 23
1 3 2 11 16
1 3 1 7 6
1 4 5 0 9
1 4 4 1 17
1 4 3 4 15
1 4 2 8 18
1 4 1 5 25
1 5 5 0 9
1 5 4 2 17
1 5 3 5 16
1 5 2 9 19
1 5 1 6 27
1 6 5 0 39
1 6 4 0 46
1 6 3 2 22
1 6 2 15 13
1 6 1 2 3
1 7 5 0 9
1 7 4 1 17
1 7 3 4 14
1 7 2 8 16
1 7 1 5 17
1 8 5 1 11
1 8 4 5 19
1 8 3 10 16
1 8 2 16 17
1 8 1 12 15
1 9 5 0 15
1 9 4 1 26
1 9 3 3 20
1 9 2 6 18
1 9 1 4 12
1 10 5 0 31
1 10 4 4 40
1 10 3 8 22
1 10 2 13 16
1 10 1 9 5
1 11 5 0 13
1 11 4 2 23
1 11 3 5 19
1 11 2 9 19
1 11 1 6 17
1 12 5 0 8
1 12 4 3 16
1 12 3 7 15
1 12 2 11 17
1 12 1 8 22
1 13 5 0 13
1 13 4 1 23
1 13 3 4 19
1 13 2 7 21
1 13 1 4 20
1 14 5 0 36
1 14 4 4 45
1 14 3 9 22
1 14 2 14 13
1 14 1 10 3
1 15 5 0 17
1 15 4 2 27
1 15 3 5 20
1 15 2 9 18
1 15 1 6 10
1 16 5 0 8
1 16 4 4 15
1 16 3 8 13
1 16 2 13 16
1 16 1 9 22
1 17 5 0 9
1 17 4 1 16
1 17 3 4 15
1 17 2 8 17
1 17 1 5 20
1 18 5 0 12
1 18 4 2 21
1 18 3 6 17
1 18 2 10 17
1 18 1 7 12
1 19 5 0 19
1 19 4 3 33
1 19 3 8 21
1 19 2 12 19
1 19 1 9 13
1 20 5 0 8
1 20 4 1 15
1 20 3 3 14
1 20 2 6 16
1 20 1 4 21
1 21 5 0 33
1 21 4 2 41
1 21 3 5 21
1 21 2 9 13
1 21 1 6 3
1 22 5 0 15
1 22 4 3 26
1 22 3 7 20
1 22 2 12 20
1 22 1 8 15
1 23 5 0 9
1 23 4 4 17
1 23 3 8 15
1 23 2 12 18
1 23 1 9 23
1 24 5 0 10
1 24 4 0 19
1 24 3 3 17
1 24 2 6 20
1 24 1 4 23
1 25 5 0 8
1 25 4 1 15
1 25 3 3 14
1 25 2 6 17
1 25 1 4 22
1 26 5 0 12
1 26 4 1 21
1 26 3 4 18
1 26 2 8 19
1 26 1 5 18
1 27 5 0 19
1 27 4 1 32
1 27 3 4 18
1 27 2 7 13
1 27 1 5 4
1 28 5 1 10
1 28 4 5 18
1 28 3 9 16
1 28 2 15 19
1 28 1 11 26
1 29 5 0 16
1 29 4 2 27
1 29 3 6 21
1 29 2 10 20
1 29 1 7 16
1 30 5 1 9
1 30 4 4 18
1 30 3 9 16
1 30 2 14 19
1 30 1 10 25
1 31 5 0 10
1 31 4 3 19
1 31 3 7 16
1 31 2 11 18
1 31 1 8 20
1 32 5 1 12
1 32 4 5 22
1 32 3 10 18
1 32 2 15 19
1 32 1 11 18
1 33 5 1 14
1 33 4 6 24
1 33 3 11 18
1 33 2 16 17
1 33 1 12 10
1 34 5 0 34
1 34 4 3 43
1 34 3 8 22
1 34 2 12 14
1 34 1 9 3
1 35 5 0 9
1 35 4 1 17
1 35 3 4 15
1 35 2 8 18
1 35 1 5 25
1 36 5 1 17
1 36 4 6 31
1 36 3 11 20
1 36 2 16 17
1 36 1 12 9

Author(s)

Issei Tsunoda tsunoda.issei1111@gmail.com

References

Example data of Jafroc software

See Also

Not dataList.Chakra.Web But dataList.Chakra.Web.orderd Not dd

Examples

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#========================================================================================
#                        Show data by table
#========================================================================================



                        viewdata(data_of_36_readers_and_a_single_modality)


plot_FPF_and_TPF_from_a_dataset(data_of_36_readers_and_a_single_modality)

####1#### ####2#### ####3#### ####4#### ####5#### ####6#### ####7#### ####8#### ####9####
#========================================================================================
#                       make this data from functions in this package
#========================================================================================



v  <- v_truth_creator_for_many_readers_MRMC_data(M=1,Q=36)
m  <- mu_truth_creator_for_many_readers_MRMC_data(M=1,Q=36)
d  <- create_dataList_MRMC(mu.truth = m,v.truth = v)


# The last object named d is the desired dataset.

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