VPC ordered multinomial (logit)
Posted: Mon May 25, 2015 1:47 pm
Hello!
I am trying to calculate the VPC for an ordered multinomial model with a logit link function. I used the threshold method (where the level-1-variance is restricted to pi^2/3), but I would also like to use the vpc.txt-macro. However, I alwasy get an error message for line 3:
calc c153=(~c151)*.c1098
pick 1 c153 b2
calc c153=(~c152)*.omega(2)*.c152
pick 1 c153 b4
seed 1
nran 5000 c154
calc c154=alog(c154*b4^0.5+b2)
aver c154 b1 b3 b2
calc c154=c154*(1-c154)
aver c154 b5 b1
calc b8=b2^2/(b1+b2^2)
---------------------------
Error detected by MLN
---------------------------
error while obeying batch file C:\...\mln125F.tmp at line number 3:
calc c153=(~c152)*.omega(2)*.c152
Dî.
---------------------------
OK
---------------------------
I put 1,0,0,0 into variable c151 and 1 into variable 152 (on the basis of the description for binomial models in the MLwiN manual) and I'm pretty sure I'm doing something wrong here. I'd appreciate if you could point me in the right direction.
Thank you very much!
Petra
I am trying to calculate the VPC for an ordered multinomial model with a logit link function. I used the threshold method (where the level-1-variance is restricted to pi^2/3), but I would also like to use the vpc.txt-macro. However, I alwasy get an error message for line 3:
calc c153=(~c151)*.c1098
pick 1 c153 b2
calc c153=(~c152)*.omega(2)*.c152
pick 1 c153 b4
seed 1
nran 5000 c154
calc c154=alog(c154*b4^0.5+b2)
aver c154 b1 b3 b2
calc c154=c154*(1-c154)
aver c154 b5 b1
calc b8=b2^2/(b1+b2^2)
---------------------------
Error detected by MLN
---------------------------
error while obeying batch file C:\...\mln125F.tmp at line number 3:
calc c153=(~c152)*.omega(2)*.c152
Dî.
---------------------------
OK
---------------------------
I put 1,0,0,0 into variable c151 and 1 into variable 152 (on the basis of the description for binomial models in the MLwiN manual) and I'm pretty sure I'm doing something wrong here. I'd appreciate if you could point me in the right direction.
Thank you very much!
Petra