[R-sig-ME] LMER - Plotting of a quadratic effect interacting with time
Boden, Matthew T.
M@tthew@Boden @end|ng |rom v@@gov
Fri Feb 1 00:05:35 CET 2019
Worked like a charm! Thanks, John.
-----Original Message-----
From: Fox, John [mailto:jfox using mcmaster.ca]
Sent: Thursday, January 31, 2019 11:57 AM
To: Boden, Matthew T. <Matthew.Boden using va.gov>
Cc: r-sig-mixed-models <r-sig-mixed-models using r-project.org>
Subject: [EXTERNAL] RE: LMER - Plotting of a quadratic effect interacting with time
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 mixed model that includes an interaction between a quadratic
> effect and time. Data attached.
>
> I fit the following:
>
> Q1 <- lmer(Patients ~ Time*FTE + Time*I(FTE^2) + (FTE | ID), data =
> SHARE)
>
> #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 FTE 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 indeed obtain Time * FTE_sq.
>
> Q2 <- lmer(Patients ~ Time*FTE + Time*FTE_sq + (FTE | ID), data =
> SHARE)
>
> 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 fixed?
I hope this helps,
John
>
> 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
> Administration
>
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