[R-sig-ME] 2 level logit, 2 REs, large sample - log likelihood returns "NaN"

[Daniel Adkins]

To clarify, the models were fit using the glmer cmd of the lme4
package. Specifically, the model with scripted as:

 proto <- glmer(hibpe ~ age + b + b_age + h + h_age + female +
female_age + bxf + hxf + numwaves + dead + nodoctor + nohosp
	+ (age| hhidpn),  nAGQ =150, family=binomial, data=hrs_data,
na.action =na.omit, verbose=TRUE)


Best,
Daniel

On Fri, Jun 10, 2011 at 4:08 AM, Daniel Adkins <deadkins at vcu.edu> wrote:
> Hi,
> I am fitting a large (j=50K, i=9K) 2-level logit with random intercept
> and age slope and 14 covariates. Model estimates become stable at
> nAGQ>=150 (large, I know). Based on simpler models (random intercept
> only, random
> slope only, ordinary logit, etc) the solution looks sound. However,
> all the fit indices return a value of "NaN", which naturally stands
> for "not a number". Why is this? This model should yield a scalar log
> likelihood, no? Any advice would be appreciated.
>
> Thanks,
> Daniel
>
> --
> Daniel E. Adkins, PhD
> Assistant Professor
> Center for Biomarker Research and Personalized Medicine
> School of Pharmacy
> Virginia Commonwealth University
> McGuire Hall, Room 216B
> 1112 East Clay Street
> Richmond, VA 23298
>



-- 
Daniel E. Adkins, PhD
Assistant Professor
Center for Biomarker Research and Personalized Medicine
School of Pharmacy
Virginia Commonwealth University
McGuire Hall, Room 216B
1112 East Clay Street
Richmond, VA 23298