How do I fix this error: "Within-imputation Estimate missing for effect ... in _Imputation_= 1 in the input PARMS= data set?"

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Posts: 1

How do I fix this error: "Within-imputation Estimate missing for effect ... in _Imputation_= 1 in the input PARMS= data set?"

Hi all,


When using PROC MIANALYZE, I am encountering this error:


ERROR: Within-imputation Estimate missing for effect ... in _Imputation_= 1 in

       the input PARMS= data set.


The PROC MIXED procedure I am using is running fine across all imputed data sets so I'm stumped. The effect in question is a 3-way interaction term with 1 of the IVs being a dummy-coded variable.

Thanks in advance for your input!

Leslie

Contributor
Posts: 50

Re: How do I fix this error: "Within-imputation Estimate missing for effect ... in _Imputation_= 1 in the input PARMS= data set?"

Posted in reply to leslie_echols

Hi,

I am also getting similar  from  proc glimmix imputation model.

ERROR: Within-imputation StdErr missing for variable  in _Imputation_= 1 in the input PARMS= data

       set.

Did you figure it out yet?

Thanks !!!

New Contributor
Posts: 3

Re: How do I fix this error: "Within-imputation Estimate missing for effect ... in _Imputation_= 1 in the input PARMS= data set?"

Posted in reply to leslie_echols

I am also receiving this error (though with _imputation_ = 8) when running MIANALYZE. I am not running any interactions. I would be very appreciative if you could share any resolution you found or if anyone else has any other suggestions. Thank you!

Occasional Contributor
Posts: 13

Re: How do I fix this error: "Within-imputation Estimate missing for effect ... in _Imputation_

Posted in reply to SASdependent

I'm also getting the same error.

Learner gyu
Learner
Posts: 1

Re: How do I fix this error: "Within-imputation Estimate missing for effect ... in _Imputation_

[ Edited ]

You could get this warning when you have more estimates in the input file than expecated by proc mianalyze. This is likely to happen if you want to get the the differences between estimates from a model with interaction term. In a standard output from analysis proc (e.g. proc glm or mixed) you could then get a lot of comparisons but most likely you wouldn't be interested in all of them. For example you could get the LS Means Difference for say levels 1 vs 2 and 2 vs 1 but you would need only one. Please try and filter the input dataset (the one from analysis procedure) for the unique comparisons only - as defined by variables in your 'class' and 'modeleffects' statements - before reading into proc mianalyze and that should allow to get the summary out of proc mianalyze and you should get rid of the warning.

 

If you were interested in summarizing all comparisons you would most likely need to sort the input dataset and use 'by' statment within proc mianalyze.

Adam
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