Running lmer results in additional quadratic fixed terms.
I don't think this is correct and I don't have a reason to include quadratic terms in the formula.
I was expecting only linear main effects and all interaction terms.
library(lmerTest)
library(sjPlot)
D <- read.csv(file = "data.csv")
D$Participant <- factor(D$Participant,order=FALSE)
D$Treatment <- factor(D$Treatment,order=TRUE,levels = c("L0","L2","L4"))
D$Timepoint <- as.numeric(D$Timepoint)
str(D)
'data.frame': 666 obs. of 6 variables:
Participant: Factor w/ 37 levels "O1","O10","O12",..: 19 21 30 4 7 13 21 21 36 36 ...
Treatment : Ord.factor w/ 3 levels "L0"<"L2"<"L4": 2 1 2 1 3 2 2 3 1 3 ...
Timepoint : num 1 1 1 1 1 1 1 1 1 1 ...
Rating : num 6 4 3 NaN 4 4 NaN 2 NaN 4 ...
Wellbeing : int 8 6 6 7 6 5 5 7 10 8 ...
mdl <- lmer(Rating ~ Treatment * Timepoint * Wellbeing + (Wellbeing | Participant), data = d,REML=F)
summary(mdl)
Here's the output of summary(mdl):
Linear mixed model fit by maximum likelihood . t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: Rating ~ Treatment * Timepoint * Wellbeing + (Wellbeing | Participant)
Data: d
AIC BIC logLik deviance df.resid
1723.3 1793.5 -845.6 1691.3 580
Scaled residuals:
Min 1Q Median 3Q Max
-3.6038 -0.6125 -0.0316 0.6088 3.6012
Random effects:
Groups Name Variance Std.Dev. Corr
Participant (Intercept) 1.30174 1.1409
Wellbeing 0.05398 0.2323 -0.83
Residual 0.82435 0.9079
Number of obs: 596, groups: Participant, 37
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 5.424e-01 3.118e-01 6.055e+01 1.739 0.08706 .
Treatment.L 4.784e-02 3.705e-01 5.490e+02 0.129 0.89729
Treatment.Q -2.209e-01 3.702e-01 5.617e+02 -0.597 0.55097
Timepoint 4.683e-02 5.515e-02 5.156e+02 0.849 0.39627
Wellbeing 2.214e-01 6.669e-02 5.828e+01 3.320 0.00156 **
Treatment.L:Timepoint -4.926e-02 9.418e-02 5.085e+02 -0.523 0.60118
Treatment.Q:Timepoint -2.663e-02 9.500e-02 5.190e+02 -0.280 0.77932
Treatment.L:Wellbeing 4.982e-02 7.670e-02 5.509e+02 0.650 0.51623
Treatment.Q:Wellbeing -1.197e-03 8.360e-02 5.684e+02 -0.014 0.98858
Timepoint:Wellbeing 9.874e-02 1.262e-02 5.273e+02 7.827 2.75e-14 ***
Treatment.L:Timepoint:Wellbeing -1.319e-02 2.019e-02 5.139e+02 -0.653 0.51390
Treatment.Q:Timepoint:Wellbeing 5.632e-04 2.256e-02 5.331e+02 0.025 0.98009
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) Trtm.L Trtm.Q Timpnt Wllbng Tr.L:T Tr.Q:T Tr.L:W Tr.Q:W Tmpn:W T.L:T:
Treatment.L -0.118
Treatment.Q 0.012 -0.098
Timepoint -0.600 0.139 -0.007
Wellbeing -0.889 0.078 0.022 0.570
Trtmnt.L:Tm 0.091 -0.873 0.095 -0.152 -0.053
Trtmnt.Q:Tm -0.006 0.092 -0.865 -0.010 -0.030 -0.110
Trtmnt.L:Wl 0.049 -0.908 0.048 -0.079 -0.004 0.804 -0.053
Trtmnt.Q:Wl 0.024 0.047 -0.908 -0.046 -0.061 -0.052 0.803 0.003
Tmpnt:Wllbn 0.532 -0.077 -0.044 -0.905 -0.615 0.082 0.070 0.016 0.106
Trtmn.L:T:W -0.046 0.775 -0.056 0.085 0.006 -0.906 0.065 -0.869 0.015 -0.014
Trtmn.Q:T:W -0.025 -0.045 0.764 0.069 0.067 0.059 -0.906 0.008 -0.864 -0.141 -0.018
The Treatment.L and Treatment.Q terms are Linear and Quadratic. Why is Quadratic added here?
Thank you.
