[R] mixed models lmer function help!!

Shelby Leonard shelby_leonard26 at yahoo.com
Mon Jun 19 18:29:30 CEST 2017

Hi,I have tumor growth curve data for a bunch of different mice in various groups. I want to compare the growth curves of the different groups to see if timing of drug delivery changed tumor growth.I am trying to run a mixed models with repeated measures over time with each mouse as a random effect with linear and quadratic terms for time.This took me a long time to figure out and I just wanted to make sure I did it correctly and I am interpreting it correctly. This is the code I ran
Rtumor<-lmer(volume~Group+Time+(1|Subject), data=Rtumor)summary(Rtumor)Rtumor.null=lmer(volume~Time+(1|Subject), data=Rtumor, REML=FALSE)Rtumor.full=lmer(volume~Group+Time+(1|Subject), data=Rtumor, REML=FALSE)anova(Rtumor.null,Rtumor.full)
Here is my output Rtumor<-lmer(volume~Group+Time+(1|Subject), data=Rtumor)> summary(Rtumor)Linear mixed model fit by REML ['lmerMod']Formula: volume ~ Group + Time + (1 | Subject)   Data: Rtumor
REML criterion at convergence: 1541.2
Scaled residuals:     Min      1Q  Median      3Q     Max -1.8006 -0.6348 -0.0658  0.3903  4.7551 
Random effects: Groups   Name        Variance  Std.Dev.  Subject  (Intercept) 3.197e-09 5.654e-05 Residual             3.348e+05 5.786e+02Number of obs: 101, groups:  Subject, 11
Fixed effects:            Estimate Std. Error t value(Intercept) -495.520    303.619  -1.632Group         24.350    115.615   0.211Time          79.653      7.886  10.101
Correlation of Fixed Effects:      (Intr) Group Group -0.933       Time  -0.300 -0.007
> Rtumor.null=lmer(volume~Time+(1|Subject), data=Rtumor, REML=FALSE)> Rtumor.full=lmer(volume~Group+Time+(1|Subject), data=Rtumor, REML=FALSE)> anova(Rtumor.null,Rtumor.full)Data: RtumorModels:Rtumor.null: volume ~ Time + (1 | Subject)Rtumor.full: volume ~ Group + Time + (1 | Subject)            Df    AIC    BIC  logLik deviance  Chisq Chi Df Pr(>Chisq)Rtumor.null  4 1576.5 1586.9 -784.24   1568.5                         Rtumor.full  5 1578.4 1591.5 -784.22   1568.4 0.0457      1     0.8307There were 50 or more warnings (use warnings() to see the first 50)

My questions are1) Did I do this correctly?2) Do I still need to run it again with quadratic terms for time?, If so, how do I do this?3) If I am understanding these results correctly, they say There is no difference between these groups on volume growth curves
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