Ming Hsu wrote:> Hi, this is my first time using the nlme package, and I ran into the
> following puzzling problem.
>
> I estimated a mixed effects model using lme, once using groupedData, once
> explicitly stating the equations. I had the following outputs. All the
> coefficients were similar, but they're always slightly different,
making me
> think that it's not due to numerical error.
>
> Also, what is the "Corr" field in the Random Effects output? Is
it the
> correlation between the various regressors?
>
> Here are the outputs.
>
> 1. Linear mixed-effects model fit by REML
> Data: groupedData(dPx ~ EMX + EMY | Session, data = X.cen)
> AIC BIC logLik
> 834.1692 862.532 -407.0846
>
> Random effects:
> Formula: ~EMX + EMY | Session
> Structure: General positive-definite
> StdDev Corr
> (Intercept) 1.0205525 (Intr) EMX
> EMX 0.2708627 1
> EMY 0.2795289 -1 -1
> Residual 5.5076376
>
> Fixed effects: dPx ~ EMX + EMY
> Value Std.Error DF t-value p-value
> (Intercept) 1.3011219 0.6807083 121 1.911423 0.0583
> EMX 0.7878296 0.2539316 121 3.102526 0.0024
> EMY -0.1566070 0.1534066 121 -1.020862 0.3094
> Correlation:
> (Intr) EMX
> EMX 0.151
> EMY -0.573 -0.092
>
> Standardized Within-Group Residuals:
> Min Q1 Med Q3 Max
> -3.00618687 -0.23680151 -0.03431868 0.15386198 6.27114243
>
> Number of Observations: 129
> Number of Groups: 6
>
> ==============================>
> 2. Linear mixed-effects model fit by REML
> Data: X.cen
> AIC BIC logLik
> 834.457 862.8199 -407.2285
>
> Random effects:
> Formula: ~EMX + EMY | Session
> Structure: General positive-definite, Log-Cholesky parametrization
> StdDev Corr
> (Intercept) 1.0101137 (Intr) EMX
> EMX 0.2108649 0.857
> EMY 0.2995491 -0.944 -0.882
> Residual 5.5104113
>
> Fixed effects: dPx ~ EMX + EMY
> Value Std.Error DF t-value p-value
> (Intercept) 1.3062194 0.6823464 121 1.914305 0.0579
> EMX 0.7612238 0.2440504 121 3.119125 0.0023
> EMY -0.1677985 0.1618076 121 -1.037025 0.3018
> Correlation:
> (Intr) EMX
> EMX 0.059
> EMY -0.552 -0.002
>
> Standardized Within-Group Residuals:
> Min Q1 Med Q3 Max
> -3.00604994 -0.24210830 -0.01660797 0.14846499 6.27931955
>
> Number of Observations: 129
> Number of Groups: 6
Could you please include the calls to lme so we can see exactly what is
being fit?
You asked about the Corr columns, those are the correlation form of the
estimated variance-covariance matrix of the random effects. Notice that
you are trying to estmate 6 variance-covariance parameters (3 variances
and 3 covariances) from information on 6 groups. In the first output
the estimated variance-covariance matrix is singlular (correlations of
-1 and +1). With so many parameters to estimate from so few groups it
is not surprising that there is difficulty.