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Asked: 2026-06-11T08:20:41+00:00

Could someone tell me what is this result when you apply mixed model with

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Could someone tell me what is this result when you apply mixed model with lme

I understand the first part but what is the second part wants to tell us (Correlation): Are they the correlation with intercept?

Fixed effects: Ratio ~ ADF + CP + FCM + DMI + DIM 
                 Value  Std.Error  DF   t-value p-value
(Intercept)  3.1199808 0.16237303 158 19.214896  0.0000
ADF         -0.0265626 0.00406990 158 -6.526603  0.0000
CP          -0.0534021 0.00539108 158 -9.905636  0.0000
FCM         -0.0149314 0.00353524 158 -4.223598  0.0000
DMI          0.0072318 0.00498779 158  1.449894  0.1491
DIM         -0.0008994 0.00019408 158 -4.634076  0.0000

Correlation: 
    (Intr) ADF    CP     FCM    DMI   
ADF -0.628                            
CP  -0.515  0.089                     
FCM -0.299  0.269 -0.203              
DMI -0.229 -0.145  0.083 -0.624       
DIM -0.113  0.127 -0.061  0.010 -0.047

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1 Answer

  1. Editorial Team

    (As I answered in the comments of your other question:)

    These are the correlations among the fixed effect estimates. If they are very high (e.g. absolute value > 0.9), they may indicate possible problems with the stability of the estimate (because you are fitting predictors with strongly collinear effects). I would say in general that if they’re less than that it’s pretty safe to ignore them. If they are higher, you might want to consider leaving out some predictors, or reducing the dimensionality of the model somehow (e.g. by PCA on the predictors — Frank Harrell’s Regression modeling strategies book is a good source), but be careful about data snooping. This r-sig-mixed-models mailing list thread gives more information.

    (This is bordering on a CrossValidated [statistics] rather than StackOverflow [programming] question …)

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