[R-sig-ME] Error in Profile likelihood based confidence intervals in glmer()

[Ben Bolker]

  I should add this to the "troubleshooting" page, but:

* There's in principle no problem at all with profiling models with
multiple random effects (other than that it's likely to be slow)
* The error message indicates that during profiling, the optimizer found
a fitted value that was significantly better (as characterized by the
'devtol' parameter) than the supposed minimum-deviance solution returned
in the first place.  You can boost the 'devtol' parameter (which is
currently set at a conservative 1e-9 ...) if you want to ignore this --
however, the non-monotonic profiles are also warning you that something
may be wonky with the profile.  It should (???) be possible to capture
the new/improved parameters that were found (although I don't know if
this is implemented in profile.merMod; I may have done it for bbmle but
not for lme4).
* the 'slice2D' methods in the bbmle package (see e.g.
http://rpubs.com/bbolker/22607 ) may be useful for exploring the
likelihood surface.

On 14-07-22 11:40 AM, Ravi Varadhan wrote:
> Hi,
> 
> I have longitudinal binary responses from a clinical trial. I am fitting
> the following random effects model in lme4::glmer.  The model is
> estimated without any problems.  However, I get an error when I try to
> compute the confidence intervals using the profile likelihood.  Does not
> the profiling approach work for more than one random effect?  Can
> someone point  out the problem?
> 
> Thanks,
> 
> Ravi
> 
>  
> 
> summary(mod2 <- glmer(imps79b ~ tx + sweek + (sweek|id), data=schiz,
> family=binomial))
> 
>  
> 
> Generalized linear mixed model fit by maximum likelihood (Laplace
> Approximation) ['glmerMod']
> 
> Family: binomial  ( logit )
> 
> Formula: imps79b ~ tx + sweek + (sweek | id)
> 
>    Data: schiz
> 
>  
> 
>      AIC      BIC   logLik deviance df.resid
> 
>   1259.4   1291.7   -623.7   1247.4     1597
> 
>  
> 
> Scaled residuals:
> 
>      Min       1Q   Median       3Q      Max
> 
> -3.03973  0.00912  0.04957  0.21372  1.45395
> 
>  
> 
> Random effects:
> 
> Groups Name        Variance Std.Dev. Corr
> 
>  id     (Intercept) 13.993   3.741        
> 
>         sweek        4.093   2.023    -0.65
> 
> Number of obs: 1603, groups:  id, 437
> 
>  
> 
> Fixed effects:
> 
>             Estimate Std. Error z value Pr(>|z|)   
> 
> (Intercept)   9.1994     1.3105   7.020 2.22e-12 ***
> 
> tx           -2.5075     0.5996  -4.182 2.89e-05 ***
> 
> sweek        -3.1344     0.4503  -6.960 3.40e-12 ***
> 
> ---
> 
> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> 
>  
> 
> Correlation of Fixed Effects:
> 
>       (Intr) tx    
> 
> tx    -0.786      
> 
> sweek -0.922  0.537
> 
>> 
> 
>  
> 
> # profiled confidence intervals
> 
>> confint(mod2, method="profile")
> 
> Computing profile confidence intervals ...
> 
> Error in zetafun(np, ns) : profiling detected new, lower deviance
> 
> In addition: Warning messages:
> 
> 1: In profile.merMod(object, signames = oldNames, ...) :
> 
>   non-monotonic profile
> 
> 2: In profile.merMod(object, signames = oldNames, ...) :
> 
>   non-monotonic profile
> 
>> 
> 
>  
> 
>  
> 
> Ravi Varadhan, Ph.D. (Environmental Eng.), Ph.D. (Biostatistics)
> 
> Associate Professor,
> 
> Division of Geriatric Medicine & Gerontology
> 
> School of Medicine,
> 
> Johns Hopkins University
> 
> Ph: 410-502-2619
> 
> Email: ravi.varadhan at jhu.edu <mailto:ravi.varadhan at jhu.edu>
> 
> http://www.jhsph.edu/research/centers-and-institutes/johns-hopkins-center-on-aging-and-health/people/Faculty_personal_Pages/Varadhan.html
> 
> 
>  
>