dd: Multiple Reader and Multiple Modality Data

In BayesianFROC: FROC Analysis by Bayesian Approaches

Description

A list, representing FROC data of MRMC. This is same as dataList.Chakra.Web .

Details

This data is based on in Chakraborty's JAFROC software in which example data exists. The author have calculated hits and false alarms from this Jafroc example data.

Contents:

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

—————————————————————————————————

ModalityID	ReaderID	Confidence levels	No. of false alarms	No. of hits.
q	m	c	f	h
--------------	-------------	------------------------	-------------------	----------------
1	1	5	0	50
1	1	4	4	30
1	1	3	20	11
1	1	2	29	5
1	1	1	21	1
1	2	5	0	15
1	2	4	0	29
1	2	3	6	29
1	2	2	15	1
1	2	1	22	0
1	3	5	1	39
1	3	4	15	31
1	3	3	18	8
1	3	2	31	10
1	3	1	19	3
1	4	5	1	10
1	4	4	2	8
1	4	3	4	25
1	4	2	16	45
1	4	1	17	14
2	1	5	1	52
2	1	4	1	25
2	1	3	21	13
2	1	2	24	4
2	1	1	23	1
2	2	5	1	27
2	2	4	1	28
2	2	3	5	29
2	2	2	30	1
2	2	1	40	0
2	3	5	2	53
2	3	4	19	29
2	3	3	31	13
2	3	2	56	2
2	3	1	42	4
2	4	5	2	9
2	4	4	0	16
2	4	3	2	22
2	4	2	30	43
2	4	1	32	14
3	1	5	1	43
3	1	4	7	29
3	1	3	13	11
3	1	2	28	6
3	1	1	19	0
3	2	5	0	18
3	2	4	1	29
3	2	3	7	21
3	2	2	7	0
3	2	1	31	0
3	3	5	7	43
3	3	4	15	29
3	3	3	28	6
3	3	2	41	7
3	3	1	9	1
3	4	5	0	10
3	4	4	2	14
3	4	3	5	19
3	4	2	24	32
3	4	1	31	23
4	1	5	1	61
4	1	4	4	19
4	1	3	18	12
4	1	2	21	9
4	1	1	23	3
4	2	5	1	16
4	2	4	1	29
4	2	3	0	34
4	2	2	11	1
4	2	1	35	0
4	3	5	6	52
4	3	4	14	29
4	3	3	37	10
4	3	2	36	4
4	3	1	18	3
4	4	5	0	10
4	4	4	2	16
4	4	3	4	23
4	4	2	18	43
4	4	1	25	15
5	1	5	0	35
5	1	4	2	29
5	1	3	19	18
5	1	2	23	9
5	1	1	18	0
5	2	5	0	17
5	2	4	2	27
5	2	3	6	24
5	2	2	10	0
5	2	1	30	0
5	3	5	2	34
5	3	4	25	33
5	3	3	40	7
5	3	2	29	13
5	3	1	24	2
5	4	5	1	12
5	4	4	1	16
5	4	3	4	21
5	4	2	24	35
5	4	1	32	15

—————————————————————————————————

Author(s)

Issei Tsunoda [e-mail]

References

Example data of Jafroc software

See Also

dataList.Chakra.Web dataList.Chakra.Web.orderd d

Examples

    viewdata(BayesianFROC::dd)


#========================================================================================
#   dd  is same as dataList.Chakra.Web,  since the following code is all TRUE
#========================================================================================

    dd$f==dataList.Chakra.Web$f







#========================================================================================
#                           Code to make the dataset dd
#========================================================================================






h<-c(
  50,30,11,5,1,15,29,29,1,0,39,31,8 ,10,3,10,8 ,25,45,14, # modality 1
  52,25,13,4,1,27,28,29,1,0,53,29,13,2 ,4,9 ,16,22,43,14, # modality 2
  43,29,11,6,0,18,29,21,0,0,43,29,6 ,7 ,1,10,14,19,32,23, # modality 3
  61,19,12,9,3,16,29,34,1,0,52,29,10,4 ,3,10,16,23,43,15, # modality 4
  35,29,18,9,0,17,27,24,0,0,34,33,7 ,13,2,12,16,21,35,15  # modality 5
)

f <-c(
  0 ,4,20,29,21,0,0,6,15,22,1 ,15,18,31,19,1,2,4,16,17,# modality 1
  1 ,1,21,24,23,1,1,5,30,40,2 ,19,31,56,42,2,0,2,30,32,# modality 2
  1, 7,13,28,19,0,1,7, 7,31, 7,15,28,41,9 ,0,2,5,24,31,# modality 3
  1, 4,18,21,23,1,1,0,11,35, 6,14,37,36,18,0,2,4,18,25,# modality 4
  0, 2,19,23,18,0,2,6,10,30, 2,25,40,29,24,1,1,4,24,32)# modality 5

a   <- m_q_c_vector_from_M_Q_C(5,4,5)

m <- a$m
c <- a$c
q <- a$q

NI<-199
NL <-142
C<-5
M<-5
Q<-4

dd <- list(
  h=h,
  f=f,
  m=m,
  c=c,
  q=q,
  NI=NI,
  NL=NL,
  M=M,
  Q=Q,
  C=C
)

BayesianFROC documentation built on Jan. 23, 2022, 9:06 a.m.