[R-sig-ME] same model runs in nlme but not lme4

[Simon Harmel]

Short but very clear. Appreciate it very much. Don't mean to make this
long, but how this likelihood profile analysis relates with fitted vs.
residual relation? Can they be at odds?

On Fri, May 22, 2020 at 5:41 PM Ben Bolker <bbolker using gmail.com> wrote:

>
>    Profile plots expressed in terms of the signed square root are straight
> lines if the log-likelihood surface is quadratic (in which case the Wald
> confidence intervals will be reliable). (I know that's very terse but I'm
> composing in haste.)
>
>   vignette("lmer", package="lme4") has a little bit.  More generally you
> can read in any advanced stats book about likelihood profiles and what they
> are/mean (section 4 of https://ms.mcmaster.ca/~bolker/emdbook/chap6A.pdf
> gives one such introduction).
> On 5/22/20 6:35 PM, Simon Harmel wrote:
>
> Many thanks, Ben. Just curious, what information do the plots at the end
> of your exactly convey?
>
> I also appreciate it if there if you could point me to a documentation in
> lme4 where I can learn more about `profile()` and its output.
>
> Many thanks, Simon
>
> On Fri, May 22, 2020 at 5:25 PM Ben Bolker <bbolker using gmail.com> wrote:
>
>>    Because lme4 is fussier than lme.  lme will fit models where the
>> variance components are jointly unidentifiable; lmer tries to detect
>> these problems and complains about them.  It's possible that this is a
>> false positive.  You can make it run by specifying
>>
>> m1 <- lmer(y~ group*year + (year|stid), data = dat,
>> control=lmerControl(check.nobs.vs.nRE="ignore"))
>>
>>    but I strongly recommend that you think about whether this might be
>> exposing problems.
>>
>>   calculating the profile suggests a little bit of weirdness.
>>
>> pp <- profile(m1,signames=FALSE)
>>
>> dd <- as.data.frame(pp)
>>
>> library(ggplot2)
>> ggplot(dd,aes(.focal,.zeta)) + geom_point() + geom_line() +
>> facet_wrap(~.par,scale="free_x")
>>
>> You can compare confint(pp) to intervals(m2); they're mostly consistent,
>> but some caution is suggested for the CIs on the correlation and the year
>> SD
>>
>>
>> On 5/22/20 5:57 PM, Simon Harmel wrote:
>> > Hi All,
>> >
>> > I was wondering why my model runs ok when I use `nlme` package but it
>> fails
>> > when I use the `lme4` package, am I missing something?
>> >
>> > Thanks, Simon
>> >
>> > #===================================
>> > library(lme4)
>> > library(nlme)
>> >
>> > dat <- read.csv('https://raw.githubusercontent.com/hkil/m/master/z.csv
>> ')
>> >
>> > m1 <- lmer(y~ group*year + (year|stid), data = dat)       ## Fails ###
>> >
>> > m2 <- lme(y~ group*year, random = ~year|stid, data = dat) ## Runs ###
>> >
>> >       [[alternative HTML version deleted]]
>> >
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