[R-sig-ME] LMER - Plotting of a quadratic effect interacting with time
m@tthew@t@boden @end|ng |rom gm@||@com
Fri Feb 1 00:12:07 CET 2019
Thank you, John. Worked like a charm.
Also, good catch on exclusion of quadratic FTE as a random effect. Made no
On Thu, Jan 31, 2019 at 11:56 AM Fox, John <jfox using mcmaster.ca> wrote:
> Dear Mathew,
> > -----Original Message-----
> > From: R-sig-mixed-models [mailto:r-sig-mixed-models-bounces using r-
> > project.org] On Behalf Of Boden, Matthew T. via R-sig-mixed-models
> > Sent: Wednesday, January 30, 2019 4:27 PM
> > To: r-sig-mixed-models using r-project.org
> > Subject: [R-sig-ME] LMER - Plotting of a quadratic effect interacting
> with time
> > Hello,
> > I have a question related to fitting and plotting a longitudinal linear
> > model that includes an interaction between a quadratic effect and time.
> > attached.
> > I fit the following:
> > Q1 <- lmer(Patients ~ Time*FTE + Time*I(FTE^2) + (FTE | ID), data =
> > #Yes, the variables are on very different scales - will take care of
> that later
> > I find a sizeable quadratic effect.
> > Fixed effects:
> > Estimate Std. Error t value
> > (Intercept) 6.760e+03 5.347e+02 12.642
> > Time 2.033e+01 1.011e+01 2.011
> > FTE 9.728e+01 8.583e+00 11.335
> > I(FTE^2) -5.155e-01 4.000e-02 -12.890
> > Time:FTE -5.560e-01 2.254e-01 -2.467
> > Time:I(FTE^2) 7.371e-03 1.052e-03 7.006
> > To plot the quadratic interaction, I attempt to use the effects package.
> > However, effects are displayed for Time x FTE, not time by FTE^2. Time x
> > is clearly not the plot that I want (I think...).
> > e1 <- effect(term="Time:I(FTE^2)", mod=Q1)
> > ed1<-as.data.frame(e1)
> > ed1
> > Time FTE fit se lower upper
> > 1 1 17 8277.635 464.3995 7366.770 9188.500
> > 2 4 17 8316.650 463.3763 7407.792 9225.508
> > ......
> > I tried a workaround, by fitting a model that included FTE^2 as a second,
> > calculated variable in the data set. Using the effects package, I do
> > obtain Time * FTE_sq.
> > Q2 <- lmer(Patients ~ Time*FTE + Time*FTE_sq + (FTE | ID), data =
> > e2 <- effect(term="Time*FTE_sq", mod=Q2)
> > ed2<-as.data.frame(e2)
> > ed2
> > Time FTE_sq fit se lower upper
> > 1 1 300 14678.1413 564.5423 13570.8582 15785.4243
> > 2 4 300 14606.9253 563.3827 13501.9166 15711.9340
> > ......
> > But the plot does not at all look like what I would expect. All lines
> > representing FTE_sq over time are straight.
> Try, plot(Effect(c("Time", "FTE"), Q1)) .
> More generally, why not fit the model as Q1 <- lmer(Patients ~
> Time*poly(FTE, 2) + (FTE | ID), data = SHARE) or Q1 <- lmer(Patients ~
> Time*poly(FTE, 2, raw=TRUE) + (FTE | ID), data = SHARE) ? Also, do you
> really want the linear term in FTE to be random and the quadratic term only
> I hope this helps,
> > ggplot(ed2, aes(x=Time, y=fit, color=FTE_sq,group=FTE_sq)) +
> > geom_point() +
> > geom_line(size=1.2) +
> > labs(title = "Time x FTE^2", x= "Time",
> > y="Patients", color="FTE^2", fill="FTE^2") + theme_classic() +
> > theme(text=element_text(size=10))
> > Does my problem (obtaining effects for FTE^2*Time and accurately plotting
> > them) relate to my use of the effects package, ggplot, both?
> > Thank you for the feedback.
> > Matthew Boden, Ph.D.
> > Senior Evaluator
> > Program Evaluation & Resource Center
> > Office of Mental Health & Suicide Prevention Veterans Health
> > _______________________________________________
> > R-sig-mixed-models using r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
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