[R-sig-ME] strange model fit- help
marKo
mtonc|c @end|ng |rom ||r|@hr
Sat Mar 14 17:10:34 CET 2020
Hi.
I have fitted a relatively complicated model to electrodermal data (a
simple resting and stimulus situation). The data summary follows.
> summary(data)
id sc t stim
g1_1 : 49 Min. :26798 Min. : 1.0 before :3201
g1_12 : 49 1st Qu.:32299 1st Qu.:123.0 after :1543
g1_13 : 49 Median :32486 Median :245.0
g1_14 : 49 Mean :32253 Mean :244.9
g1_15 : 49 3rd Qu.:32587 3rd Qu.:367.0
g1_2 : 49 Max. :32761 Max. :489.0
(Other):4450
id (person), and stim are factors, t is time (in s) and sc is skin
conductance level. Sc distribution is quite negatively asymmetrical at
the dataset level, although not that bad at the id level. As the
stimulus occur at a specified time, those two variables are correlated
(0.81).
The model follows.
m1<-lmer(sc~1+t+I(t^2)+stim+stim:t+stim:I(t^2)+(1+t+I(t^2)+stim+stim:t+stim:I(t^2)|id),
data=data)
Here goes the summary.
> summary(m1)
Linear mixed model fit by maximum likelihood ['lmerMod']
Formula: sc ~ 1 + t + I(t^2) + stim + stim:t + stim:I(t^2) + (1 + t +
I(t^2) + stim + stim:t + stim:I(t^2) | id)
Data: data
AIC BIC logLik deviance df.resid
62325.9 62506.9 -31134.9 62269.9 4716
Scaled residuals:
Min 1Q Median 3Q Max
-24.3783 -0.1551 -0.0074 0.1392 12.5288
Random effects:
Groups Name Variance Std.Dev. Corr
id (Intercept) 4.681e+04 2.164e+02
t 7.925e+00 2.815e+00 1.00
I(t^2) 2.559e-05 5.059e-03 -0.87 -0.87
stim.L 1.591e+05 3.989e+02 -0.12 -0.12 0.17
t:stim.L 1.105e+00 1.051e+00 -0.58 -0.58 0.78 0.33
I(t^2):stim.L 2.367e-05 4.865e-03 0.06 0.06 -0.21 -0.76 -0.45
Residual 2.049e+04 1.432e+02
Number of obs: 4744, groups: id, 97
Fixed effects:
Estimate Std. Error t value
(Intercept) 2.960e+04 1.637e+02 180.85
t 1.291e+01 8.493e-01 15.20
I(t^2) -1.579e-02 1.110e-03 -14.21
stim.L -3.956e+03 2.329e+02 -16.98
t:stim.L 2.047e+01 1.136e+00 18.01
I(t^2):stim.L -2.477e-02 1.478e-03 -16.76
Correlation of Fixed Effects:
(Intr) t I(t^2) stim.L t:st.L
t -0.886
I(t^2) 0.811 -0.966
stim.L 0.972 -0.930 0.868
t:stim.L -0.989 0.911 -0.826 -0.973
I(t^2):st.L 0.917 -0.858 0.761 0.870 -0.947
The fit of the model is quite good (pseudo r2 is 0.96), but have some
problems:
1: quite “extreme” residuals (-24.3783, 12.5288)
2: quite high correlations among random effects
3: lousy qqplot (apart from the perfect fit on the from -2 to +2 std
normal quantiles)
Help please? What is wrong with the model (something is, I’m sure).
--
Marko Tončić, PhD
Postdoctoral research assistant
University of Rijeka
Faculty of Humanities and Social Sciences
Department of Psychology
Sveucilisna avenija 4, 51000 Rijeka, CROATIA
e-mail: mtoncic using ffri.hr
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