Bivariate threshold model with 2 different thresholds
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Havinginsight
Joined: 07/11/2011
| Attachment | Size |
|---|---|
| Bivariate_ASD_SK_Forum.R | 4.73 KB |
| asdtrainingfile.dat | 20.11 KB |
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Hello!
I'm trying to run a bivariate model to estimate ACE for autism and social skills. Autism has 1 threshold and social skills 5.
Do I need to specify both thresholds for the model? At the moment the script I've adapted does not do that. However, it doesn't run and returns the following error message:
"twinSat' exited abnormally with the error message: Objective function returned a value of NaN at iteration 0.1."
I want the threshold for diagnosis of autism to be above 2.3 score cut off point.
It has been pointed out to me that I am not setting the values right, but after trying different starting values and increments I still get the same error message.
Could anyone help, pretty please!??
MANY THANKS IN ADVANCE.
Bea
Hmmm
I thought I had it - matrix Low1 should be declared as Lower, not Full. Having fixed that and mxRun with unsafe=T it still fails. The covariance matrices look positive definite, the thresholds are in order, means are zero... I am a bit stuck too, will think about it. But do make the change to Low1. Oh, now I see. You need to mxFactor the ASD variable to have only two levels. However, it then becomes a problem that the expected correlation matrix of the MZ's can go negative definite (because you've individually estimated the correlations). I think you may need to head to Cholesky land or similar in order to constrain the correlation matrix to stay positive definite.
Running twinSat
Warning message:
The job for model 'twinSat' exited abnormally with the error message: Objective function returned a value of NaN at iteration 17.18.
> twinSatSumm <- summary(twinSatFit)
> round(twinSatFit@output$estimate,4)
r12 MZ.Block2[1,2] MZ.Block2[2,2] tv2 i12 i22 i32 i42 DZ.Block3[1,2]
0.4931 0.2586 0.7268 -0.6886 0.5972 0.4923 0.5832 0.5892 0.1209
DZ.Block3[2,2]
0.5041
> twinSatSumm
data:
$MZ.data
ASD1 SSP1 ASD2 SSP2
0 :32 0 : 8 0 :32 0 : 9
1 :20 1 : 8 1 :20 1 :11
NA's: 2 2 : 4 NA's: 2 2 : 5
3 : 8 3 : 9
4 : 7 4 : 3
5 : 9 5 : 7
NA's:10 NA's:10
$DZ.data
ASD1 SSP1 ASD2 SSP2
0 :86 0 :19 0 :96 0 :19
1 :54 1 :15 1 :44 1 :22
NA's:11 2 :27 NA's:11 2 :20
3 :19 3 :20
4 :20 4 :22
5 :20 5 :18
NA's:31 NA's:30
free parameters:
name matrix row col Estimate Std.Error lbound ubound
1 r12 MZ.expCorPhmz 1 2 0.4930889 8.487983e-314 -0.99 0.99
2 MZ.Block2[1,2] MZ.Block2 1 2 0.2586425 NaN -0.99 0.99
3 MZ.Block2[2,2] MZ.Block2 2 2 0.7267790 NaN -0.99 0.99
4 tv2 MZ.V2thmz 1 1 -0.6886430 NaN -4
5 i12 MZ.V2thmz 2 1 0.5972055 4.243992e-314 0.001
6 i22 MZ.V2thmz 3 1 0.4923450 NaN 0.001
7 i32 MZ.V2thmz 4 1 0.5831866 NaN 0.001
8 i42 MZ.V2thmz 5 1 0.5891707 NaN 0.001
9 DZ.Block3[1,2] DZ.Block3 1 2 0.1208841 NaN -0.99 0.99
10 DZ.Block3[2,2] DZ.Block3 2 2 0.5041306 3.458460e-323 -0.99 0.99
observed statistics: 713
estimated parameters: 10
degrees of freedom: 703
-2 log likelihood: NaN
saturated -2 log likelihood: NA
number of observations: 205
chi-square: NaN
p: NaN
Information Criteria:
df Penalty Parameters Penalty Sample-Size Adjusted
AIC: NaN NaN NA
BIC: NaN NaN NaN
CFI: NA
TLI: NA
RMSEA: NA
timestamp: 2012-10-17 16:42:20
frontend time: 0.1406462 secs
backend time: 0.2088509 secs
independent submodels time: 2.908707e-05 secs
wall clock time: 0.3495262 secs
cpu time: 0.3495262 secs
openmx version number: 999.0.0-2174
>
>
> &&&&&&&&&&&&&&&&
Error: unexpected '&&' in "&&"
> twinSatFit$MZ.expCorMZ
mxAlgebra 'expCorMZ'
@formula: rbind(cbind(expCorPhmz, Block2), cbind(Block2, expCorPhmz))
@result:
[,1] [,2] [,3] [,4]
[1,] 1.0000000 0.4930889 0.8000000 0.2586425
[2,] 0.4930889 1.0000000 0.2586425 0.7267790
[3,] 0.8000000 0.2586425 1.0000000 0.4930889
[4,] 0.2586425 0.7267790 0.4930889 1.0000000
dimnames: NULL
> twinSatFit$DZ.expCorDZ
mxAlgebra 'expCorDZ'
@formula: rbind(cbind(expCorPhdz, Block3), cbind(Block3, expCorPhdz))
@result:
[,1] [,2] [,3] [,4]
[1,] 1.0000000 0.4930889 0.4000000 0.1208841
[2,] 0.4930889 1.0000000 0.1208841 0.5041306
[3,] 0.4000000 0.1208841 1.0000000 0.4930889
[4,] 0.1208841 0.5041306 0.4930889 1.0000000
dimnames: NULL
> eigen(twinSatFit$MZ.expCorMZ@result)
$values
[1] 2.5160118430 1.0107671725 0.4738982179 -0.0006772334
$vectors
[,1] [,2] [,3] [,4]
[1,] -0.5120166 -0.4876874 -0.4598132 0.5371888
[2,] -0.4876874 0.5120166 -0.5371888 -0.4598132
[3,] -0.5120166 -0.4876874 0.4598132 -0.5371888
[4,] -0.4876874 0.5120166 0.5371888 0.4598132
> eigen(twinSatFit$DZ.expCorDZ@result)
$values
[1] 2.0682420 0.9237634 0.8358886 0.1721060
$vectors
[,1] [,2] [,3] [,4]
[1,] -0.4784095 -0.5335107 0.5206960 0.4640758
[2,] -0.5206960 -0.4640758 -0.4784095 -0.5335107
[3,] -0.4784095 0.5335107 0.5206960 -0.4640758
[4,] -0.5206960 0.4640758 -0.4784095 0.5335107
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