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Variable confounds with residual

Hi,

l am attempting to analyse data for an interlab study with a mixed model, its a nested design with 5 variables, the dependant variable is titers, the structure of my analysis is as follows

Fixed Effect

Sample (30 of)

Random Effects

Sample*Lab (3 levels)
Sample*Day (3 Levels)
Sample*Run (2 Levels)
Replicate[Sample,Lab,Day,Run] (replicate has 2 levels)
Sample*Lab*Day

l get the error message that Replicate[Sample,Lab,Day,Run] confounds with residual, this is the first time i have encountered this message and i am not sure what its telling me, has anyone encountered this before and how did they overcome it??

Thanks

Mick

Analytics

Re: Variable confounds with residual

Thought l would reply to my own post, i think i have over complicated things, l have retried with a simplified model

Sample Fixed Effect

Sample*Lab & Random Lab Variance

Run[Sample,Lab,Day] & Random Run Variance

Sample*Lab*Day & Random Interaction between Lab and Day

Sample*Day & Random Day Variance

the R2 is great, no convergence issues, no confounding, and is easy to explain.

Any input would be appreciated

Re: Variable confounds with residual

The residual is automatically the lowest random effect. If residual of each observation is actually the same as the replicate level of random effect, then they are confounded. Leave replicate out of the model. The residual estimate is the replicate estimate.