Hello,

I am running two different regression models. The first runs fine, but the second returns the Mx Status Red error. The Model 2 script is the same as Model 1, just with different data. Any help would be appreciated.

Thanks,

Jeff

# begin script

> ###########

> # Model 1 #

> ###########

>

>

> R.smp1 <- matrix(c(1.0000000, 0.7534779, 0.3378677,

+ 0.7534779, 1.0000000, 0.3757937,

+ 0.3378677, 0.3757937, 1.0000000),3,3)

>

> pred <- c("x1","x2"); out <- "y"

> varnames <- c(pred,out)

> dimnames(R.smp1) <- list(varnames,varnames)

>

> n1 <- 50 # sample size

>

> m1 <- mxModel("Regression of y on X (standardized)",

+ type="RAM",

+ manifestVars=varnames,

+

+ mxPath(from=pred,to=out,

+ arrows=1,

+ free=TRUE,values=.3,

+ labels=c("b1","b2")),

+

+ mxPath(from=out,arrows=2,

+ free=TRUE,values=.8,

+ labels=c("VarE")),

+

+ mxPath(from=pred,to=pred,arrows=2,

+ all=TRUE,free=TRUE,

+ values=.2),

+

+ mxPath(from=pred, arrows=2,

+ free=TRUE, values=1),

+

+ mxCI(c("b1","b2")),

+

+ mxData(observed=R.smp1,type="cov",numObs=n1))

>

> m1.run <- mxRun(m1,intervals=TRUE)

Running Regression of y on X (standardized)

>

>

> ###########

> # Model 2 #

> ###########

>

>

> R.smp2 <- matrix(c(1.00000000, 0.97364484, -0.26357364,

+ 0.97364484, 1.00000000, -0.06512353,

+ -0.26357364, -0.06512353, 1.00000000),3,3)

> dimnames(R.smp2) <- list(varnames,varnames)

>

> n2 <- 100

>

> m2 <- mxModel("Regression of y on X (standardized)",

+ type="RAM",

+ manifestVars=varnames,

+

+ mxPath(from=pred,to=out,

+ arrows=1,

+ free=TRUE,values=.3,

+ labels=c("b1","b2")),

+

+ mxPath(from=out,arrows=2,

+ free=TRUE,values=.8,

+ labels=c("VarE")),

+

+ mxPath(from=pred,to=pred,arrows=2,

+ all=TRUE,free=TRUE,

+ values=.2),

+

+ mxPath(from=pred, arrows=2,

+ free=TRUE, values=1),

+

+ mxCI(c("b1","b2")),

+

+ mxData(observed=R.smp2,type="cov",numObs=n2))

>

> m2.run <- mxRun(m2,intervals=TRUE)

Running Regression of y on X (standardized)

Warning message:

In model 'Regression of y on X (standardized)' NPSOL returned a non-zero status code 6. The 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)

Please make use of the search function in both the forum and the wiki to investigate this error. It turns out that it is commonly reported and usual course of action has been addressed in several posts. Try re-running the model per

http://openmx.psyc.virginia.edu/wiki/errors

That it is widely reported, however, suggests that OpenMx itself should be doing a better job of telling people what to do when they get such a warning.