| sim.gRoeMetz {iMRMC} | R Documentation | 
Simulate an MRMC data set of an ROC experiment comparing two modalities
Description
This procedure simulates an MRMC data set of an ROC experiment comparing two modalities.
It is based on Gallas2014_J-Med-Img_v1p031006, which generalizes of the model in
Roe1997_Acad-Radiol_v4p298 and Roe1997_Acad-Radiol_v4p587. Specifically, it allows
the variance components to depend on the truth and the modality. For the simpler
Roe and Metz model, you can enter the smaller set of parameters into
sim.gRoeMetz.config and get back the larger set of parameters and then
used with this function.
Usage
sim.gRoeMetz(config)
Arguments
| config | [list] of simulation parameters:
 
 Experiment labels and size
 
 modalityID.A: [chr] label modality A
 modalityID.B: [chr] label modality B
 nR: [num] number of readers
 nC.neg: [num] number of signal-absent cases
 nC.pos: [num] number of signal-present cases
 There are six fixed effects:
 
 mu.neg: [num] signal-absent (neg, global mean)
 mu.pos: [num] signal-present (pos, global mean)
 mu.Aneg: [num] modality A signal-absent (Aneg, modality effect)
 mu.Bneg: [num] modality B signal-absent (Bneg, modality effect)
 mu.Apos: [num] modality A signal-present (Apos, modality effect)
 mu.Bpos: [num] modality B signal-present (Bpos, modality effect)
 There are six random effects that are independent of modality
 
 var_r.neg: [num] variance of random reader effect
 var_c.neg: [num] variance of random case effect
 var_rc.neg: [num] variance of random reader by case effect
 var_r.pos: [num] variance of random reader effect
 var_c.pos: [num] variance of random case effect
 var_rc.pos: [num] variance of random reader by case effect
 There are six random effects that are specific to modality A
 
 var_r.Aneg: [num] variance of random reader effect
 var_c.Aneg: [num] variance of random case effect
 var_rc.Aneg: [num] variance of random reader by case effect
 var_r.Apos: [num] variance of random reader effect
 var_c.Apos: [num] variance of random case effect
 var_rc.Apos: [num] variance of randome reader by case effect
 There are six random effects that are specific to modality B
 
 var_r.Bneg: [num] variance of random reader effect
 var_c.Bneg: [num] variance of random case effect
 var_rc.Bneg: [num] variance of random reader by case effect
 var_r.Bpos: [num] variance of random reader effect
 var_c.Bpos: [num] variance of random case effect
 var_rc.Bpos: [num] variance of randome reader by case effect
 | 
Details
The simulation is a linear model with six fixed effects related to
modality and truth and 18 normally distributed independent random effects
for readers, cases, and the interaction between the two. Here is the linear model:
L.mrct = mu.t + mu.mt 
+ reader.rt + case.ct + readerXcase.rct 
+ modalityXreader.mrt + modalityXcase.mct + modalityXreaderXcase.mrct 
-  m=modality (levels: A and b)
 
-  t=truth (levels: neg and Pos)
 
-  mu.t is the global mean for t=neg and t=pos cases
 
-  mu.mt is the modality specific fixed effects for t=neg and t=pos cases
 
-  the remaining terms are the random effects: all independent normal random variables
 
Value
dFrame.imrmc   [data.frame] with (nC.neg + nC.pos)*(nR+1) rows including
-  readerID: [Factor] w/ nR levels "reader1", "reader2", ...
 
-  caseID: [Factor] w/ nC levels "case1", "case2", ...
 
-  modalityID: [Factor] w/ 1 level config$modalityID
 
-  score: [num] reader score
 
Note that the first nC.neg + nC.pos rows specify the truth labels for each case.
For these rows, the readerID must be "truth" or "-1"
and the score must be 0 for negative cases and 1 for postive cases.
[Package iMRMC version 1.2.0 ]