Getting this error

Error: The observed correlation matrix is not 1's along the diagonal

from the statement

mxData(cor, type="cor", numObs=1656)

but looking at the data matrix indicates that its diagonal consists of 1's

> diag(cor)

SOF IWF PWF FSC FSF EF GPA

1 1 1 1 1 1 1

cor

SOF IWF PWF FSC FSF EF GPA

SOF 1.00000000 -0.310734680 0.02337843 -0.01050081 0.324939442 -0.49945847 0.83664278

IWF -0.31073468 1.000000000 0.09947420 -0.03052640 0.001136279 0.49532944 -0.10899843

PWF 0.02337843 0.099474205 1.00000000 -0.61560751 -0.628812462 0.11562605 -0.21215413

FSC -0.01050081 -0.030526399 -0.61560751 1.00000000 0.048027377 -0.41138615 -0.12042060

FSF 0.32493944 0.001136279 -0.62881246 0.04802738 1.000000000 -0.13170374 0.52886839

EF -0.49945847 0.495329442 0.11562605 -0.41138615 -0.131703740 1.00000000 -0.04665071

GPA 0.83664278 -0.108998427 -0.21215413 -0.12042060 0.528868389 -0.04665071 1.00000000

Full code to make model copied below

#install.packages("ggm")

require(ggm)

cor = rcorr(7)

manifests = c("SOF", "IWF", "PWF", "FSC", "FSF", "EF", "GPA")

dimnames(cor)<-list(manifests,manifests)

fit1<- mxModel("model", type="RAM",

manifestVars = manifests,

mxPath(from = manifests, arrows=2),

mxPath(from = "PWF", to=c("FSF","FSC"), arrows=1),

mxPath(from = "PWF", to="IWF" , arrows=1),

mxPath(from = "PWF", to="SOF" , arrows=1),

mxPath(from = "SOF", to="IWF" , arrows=1),

mxPath(from = "SOF", to=c("FSF","FSC") , arrows=1),

mxPath(from= "IWF", to=c("FSF","FSC") , arrows=1),

mxPath(from= "FSC", to="EF" , arrows=1),

mxPath(from= "FSF", to="EF" , arrows=1),

mxPath(from= "EF" , to="GPA" , arrows=1),

mxData(cor, type="cor", numObs=1656)

)

Interesting. It appears that the diagonal of the correlation matrix has entries that are very slightly not equal to one:

An easy way to run the model is just to set

`diag(cor) <- 1`

. An easy improvement of the current situation would be to augment the error message to say, "The observed correlation matrix is almost equal to, but not identical, to 1's along the diagonal." The larger question is whether or not to allow these input matrices? My inclination is not to allow them, since the eplison that we would need to choose for approximate equality is an arbitrary value.nice one michael!

I found that taking cov2cor() made the error go away, but the fact that diag() printed 1 with no decimals threw me off the scent...

Reporting the error as you suggest would be fantastic, perhaps noting that cov2cor() can fix this if it is an error...

t

yep, because the penultimate line of cov2cor is:

r[cbind(1L:p, 1L:p)] <- 1

which uses the matrix indexes for diagonals and sets them to 1 :)

cleaner 'fix' then cov2cor would just be: diag(cor) <- 1