# Random effect with zero variance

I measured explorative behaviour of 29 individuals repeatedly (at least twice) since I’m interested in how consistent they are through time. It seems, based on the attached plot, that there are clear differences between individuals in exploration. However, when I use a Linear mixed effect model with ID as a random variable

Model1<-lmer(Explo~1+(1|ID) ,data=OnlyMJ)


Linear mixed model fit by REML t-tests use Satterthwaite approximations to degrees of freedom [lmerMod] Formula: Explo ~ 1 + (1 | ID) Data: OnlyMJ

REML criterion at convergence: 254.5

Scaled residuals: Min 1Q Median 3Q Max -1.0565 -0.6838 -0.1794 0.3894 4.0976

Random effects: Groups Name Variance Std.Dev. ID
(Intercept) 0.000 0.00 Residual 2.754 1.66
Number of obs: 66, groups: ID, 30

Fixed effects: Estimate Std. Error df t value Pr(>|t|) (Intercept) -0.02594 0.20428 65.00000 -0.127 0.899

The random effect (between individual variance in exploration) is zero. This seems very weird and I can’t explain this. I have no idea what the problem is.

• What output do you get from ranef(Model1)? Sep 8, 2016 at 14:27
• see tinyurl.com/glmmFAQ, search for "random effect variances estimated as zero" ... Sep 8, 2016 at 14:29
• These boxplots are deceptive, because almost all are representing only two values!
– whuber
Sep 8, 2016 at 14:50