Dear Axel,
> On May 15, 2020, at 7:39 PM, Axel Urbiz <[email protected]> wrote:
>
> Dear John,
>
> Thank you for your response.
>
> My apologies as I’m only recently getting exposed to mixed-model. My
> understanding, is that the model specified below also has random intercepts
> and slope, as they vary by Subject. `coef(fm1)` shows this. I was looking to
> plot the fitted splines by Subject.
>
> Sorry if my interpretation is incorrect.
There's no need to apologize.
The functions in the effects package compute and graph fixed effects for mixed
models. You could compute and graph the BLUP for the fitted spline for each
subject (see below) but it's not what the effects package does.
I think that the following does what you want:
-------- snip ----------
subjects <- levels(sleepstudy$Subject)
fits <- matrix(0, length(subjects), 10)
rownames(fits) <- subjects
for (subject in subjects){
fits[subject, ] <- predict(fm1, newdata=data.frame(Subject=subject, Days=0:9))
}
plot(c(0, 10), range(fits), type="n", xlab="Days", ylab="Reaction")
for (subject in subjects) lines(0:9, fits[subject, ])
-------- snip ----------
Best,
John
>
> Best,
> Axel.
>
>
>
>> On May 15, 2020, at 5:51 PM, Fox, John <[email protected]> wrote:
>>
>> Dear Axel,
>>
>> There only one fixed effect in the model, ns(Days, 3), so I don't know what
>> you expected.
>>
>> Best,
>> John
>> --------------------------------------
>> John Fox, Professor Emeritus
>> McMaster University
>> Hamilton, Ontario, Canada
>> Web: socialsciences.mcmaster.ca/jfox/
>>
>>
>>
>>> -----Original Message-----
>>> From: Axel Urbiz <[email protected]>
>>> Sent: Friday, May 15, 2020 5:33 PM
>>> To: Fox, John <[email protected]>; [email protected]
>>> Subject: "effects" package with "lme4"
>>>
>>> Hello John and others,
>>>
>>> I’d appreciate your help as I’m trying to plot the effect of predictor
>>> “Days” on Reaction by Subject. I’m only getting one plot in the example
>>> below.
>>>
>>> ### Start example
>>>
>>> library(lme4)
>>> library(splines)
>>> data("sleepstudy")
>>>
>>> fm1 <- lmer(Reaction ~ ns(Days, 3) + (ns(Days, 3) | Subject), sleepstudy)
>>> coef(fm1)
>>> plot(allEffects(fm1))
>>>
>>> ### End example
>>>
>>> Thanks,
>>> Axel.
>
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