I'm running a factor analysis, which I have done before using EQS, with OpenMx and finding an error. The code and the output are below. I'd appreciate any diagnostics and directions!

Regards,
Carlos.

load library

require(OpenMx)

data

AttractivenessDataRaw <- read.table("/home/pos/carlosdenner/Desktop/logattractiveness.txt",header=TRUE)
names(AttractivenessDataRaw)

model specification

AttractivenessFactorModel<-mxModel("Attractiveness Factor Model",
type="RAM",
mxData(
observed=AttractivenessDataRaw,
type="raw"),
manifestVars=c("pageviews","downloads","members"),
latentVars="attractiveness",
# residual variances
mxPath(from=c("pageviews","downloads","members"),
arrows=2,
free=TRUE,
values=c(1,1,1),
labels=c("e1","e2","e3")
),
# latent variance
mxPath(from="attractiveness",
arrows=2,
free=TRUE,
values=1,
labels ="varAttractiveness"
),
# factor loadings
mxPath(from="attractiveness",
to=c("pageviews","downloads","members"),
arrows=1,
free=c(FALSE,TRUE,TRUE),
values=c(1,1,1),
labels =c("l1","l2","l3")
),
# means
mxPath(from="one",
to=c("pageviews","downloads","members","attractiveness"),
arrows=1,
free=c(TRUE,TRUE,TRUE,FALSE),
values=c(1,1,1,0),
labels =c("meanpageviews","meandownloads","meanmembers",NA)
)
) # close model

AttractivenessFactorFit <- mxRun(AttractivenessFactorModel)

Output:
Running Attractiveness Factor Model
Warning message:
In model 'Attractiveness Factor Model' NPSOL returned a non-zero status code 6. model does not satisfy the first-order optimality conditions to the required accuracy, and no improved point for the merit function could be found during the final linesearch (Mx status RED)