Hi everyone,

Hope you are enjoying the winter break!

I am trying to estimate a derived parameter using mxEval() and mxSE(). The function mxEval() works well, but mxSE() reports a warning message as below and produces NA for the standard error.

"1: In mxSE(paste0("instant_rate_est", j), model = model, ... :

Some diagonal elements of the repeated-sampling covariance matrix of the point estimates are less than zero or NA.

I know, right? Set details=TRUE and check the 'Cov' element of this object. "

I installed the last version of OpenMx and here are the lines I am using:

Loads1 <- mxMatrix("Full", 1, 1, free = F, labels = paste0(data.T1), name = "t1")

Loads2 <- mxMatrix("Full", 1, 1, free = F, labels = paste0(data.T2), name = "t2")

midT1 <- mxAlgebra(t2 - t1, name = mid_t1)

slp_est1 <- mxAlgebraFromString(paste0("mueta2 * mid_t1"), name = paste0("instant_rate_est", 1))

In the formula, "mueta2" is a free parameter, so my guess is it was caused by the definition variables "data.T1" and "data.T2", but I am not sure. Any advice on how to avoid such warning messages and have SE values?

Thank you so much for your attention.

Hi Veronica,

`mxSE()`

should, in theory, work for models with definition variables. Did you do what the warning/error message suggested?`mxSE()`

starts from the standard errors of the model and then makes a linear approximation to the standard errors of arbitrary algebraic functions of those free parameters. The warning/error message is saying the at least one of original standard errors is zero or NA. Look at the output from`mxSE(..., details=TRUE)`

; in particular at the`Cov`

part. Is one of the diagonal elements zero or NA? Alternatively, you could look at the`summary()`

of the model and see if one of the parameters has an NA or zero standard error.If the model does not have all of its standard errors then you can't really use

`mxSE`

. The NA just propagates through and makes everything it touches an NA.Mike