[R-sig-ME] unequal spacing in repeated measures

[Ben Bolker]

Matthew P. Dekar wrote:
> I would appreciate any advice in regards to the handling of unequal
> spacing in repeated measures regression with mixed models.  I sampled
> crayfish with funnel traps and measured environmental predictor
> variables monthly for two years in 12 stream pools.  Data are
> presented in terms of the average number of crayfish per trap per
> pool (response variable = catch-per-unit-effort = cpue).  However,
> the sampling interval was not fixed so I created a continuous time
> variable (day) indicating the number of days elapsed from the first
> sampling occasion (1,35,55,...,643).  As an example, I modeled cpue
> in a repeated measures framework with a single predictor variable
> (stream temperature = temp), pool as the subject/random variable, and
> day was included using a spatial covariance structure (Exponential =
> corExp) in lme following:
> 
> cpu1<-lme(cpue~temp, random=~1 | pool, data=CPU, method = "ML") 
> cpu2<- update(cpu1, correlation = corExp(form=~day))
> 
> Is this an appropriate usage of spatial covariance structures?  Can
> the above analysis be replicated in lmer?  Thanks very much for your
> time.
> 

  You should use correlation=corCAR1(form=~day) for a continuous
time covariate.

  You can't do this in lmer (yet, or for a while) -- Doug Bates has
stated that implementing correlation structures a la nlme is lower
on his list than working out other issues.

  good luck,
   Ben Bolker