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03-16-2017 06:03 PM

Can anyone provide me with some insight on why the random statement has an estimate of 0?

I have multiple data sets with the same issue (although the code runs just fine on others). The number of replicates ranges from 4 to 6 between the sets (most have 5) with 5 or more levels of treatment.

I am running a proc mixed model and using the random statement to control for replicate (and also to see if there is an effect).

This is the output I get for the random section:

Covariance Parameter Estimates Cov ParmEstimate StandardError Z Value Pr > Z

rep 0 . . .

Residual 0.000250 0.000072 3.460 .0003

Are there any tips or tricks that would allow me to get an estimate in this section?

Any advice would be appreciated.

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Solution

03-22-2017
06:08 AM

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03-16-2017 08:26 PM

Is the MIXED procedure also telling you that the estimated G matrix is not positive definite?

Most likely, this result implies that there is little variation among *rep*s for this response variable. The procedure has set the estimate to zero (hence, the SE is missing) and continued on its merry way. See Section III in this paper

http://support.sas.com/resources/papers/proceedings12/332-2012.pdf

In the documentation

under Parameter Constraints, you'll find:

"For some data sets the final estimate of a parameter might equal one of its boundary constraints. This is usually not a cause for concern, but it might lead you to consider a different model. For instance, a variance component estimate can equal zero; in this case, you might want to drop the corresponding random effect from the model. However, be aware that changing the model in this fashion can affect degrees-of-freedom calculations.

If that doesn't seem to be the reason, then you'll want to post your code and an example dataset so that people here have more to work with.

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Solution

03-22-2017
06:08 AM

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03-16-2017 08:26 PM

Is the MIXED procedure also telling you that the estimated G matrix is not positive definite?

Most likely, this result implies that there is little variation among *rep*s for this response variable. The procedure has set the estimate to zero (hence, the SE is missing) and continued on its merry way. See Section III in this paper

http://support.sas.com/resources/papers/proceedings12/332-2012.pdf

In the documentation

under Parameter Constraints, you'll find:

"For some data sets the final estimate of a parameter might equal one of its boundary constraints. This is usually not a cause for concern, but it might lead you to consider a different model. For instance, a variance component estimate can equal zero; in this case, you might want to drop the corresponding random effect from the model. However, be aware that changing the model in this fashion can affect degrees-of-freedom calculations.

If that doesn't seem to be the reason, then you'll want to post your code and an example dataset so that people here have more to work with.

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03-16-2017 10:51 PM

If you could use PROC GLIMMIX , try : random int time / type=chol