[R-sig-ME] Modelling random effects for only part of the observations (in lme4)

[Ben Bolker]

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On 15-01-16 04:37 AM, Hufthammer, Karl Ove wrote:
> Thierry ONKELINX wrote:
>> Dear Karl Ove,
>> 
>> (X|G) is equivalent to (1 + X|G). Or mathematically: b_0i +
>> b_1iX. But you need b_1iX.
>> 
>> The solution is to remove the random intercept (0 + X|G)
>> 
>> I would go for lmer(y ~ arm + (0 + b|gr2))
> 
> Great! Thanks. This works perfectly.
> 
> And I now understand what's going on in the formula too. The lme4 
> syntax is rather elegant. :)

  Can we quote you on that?

  :-)

> 
> The fixed effect estimates are near identical to estimates based
> on lm(y ~ arm), while the standard errors are different, which is 
> exactly what would be expected. The reason they're not exactly 
> identical is that one treatment group had only 2 subjects, so the 
> design was not perfectly balanced. If I change it to a balanced 
> design (equal number of subjects in each treatment group), the 
> estimates are identical between lmer and lm (while of course the 
> standard errors still differ).
> 

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