[R-sig-ME] na.action in lmer()

[Ben Bolker]

  You shouldn't need to do anything special, since the data are written
out in a long format, e.g.

Patient  time   y
1           0   0.1
1           1   0.3
...
2           0   0.1
2           1   NA
2           2   0.3
...

  Unlike in the classic MANOVA setup where the responses from an
individual are all considered part of the same observation (and hence an
NA screws things up badly), this is just handled automatically/naturally
in the mixed-model context.

  The only difference between na.omit() and na.exclude() is whether NA
values are inserted into appropriate places in the downstream
residual/prediction calculations.  (g)lmer can't do anything with
observations containing NA values, but 'observation' means (in this
case) 'patient-time combination', not 'patient'.

  (Do you mean REML=FALSE ... ?)


On 16-04-21 05:19 PM, Ravi Varadhan wrote:
> Hi,
> 
> I am fitting a model like this with random intercept and random slope
> using lme4::lmer.
> 
> lmer(y ~ time + (time|Patient), REML="FALSE", na.action=na.omit)
> 
> The `na.omit' option is the default. However, I would like to include
> patients with one or missing values in their time trajectory.  Which
> NA handling option would I use?
> 
> Thank you, Ravi
> 
> Ravi Varadhan, Ph.D. (Biostatistics), Ph.D. (Environmental Engg) 
> Associate Professor,  Department of Oncology Division of
> Biostatistics & Bionformatics Sidney Kimmel Comprehensive Cancer
> Center Johns Hopkins University 550 N. Broadway, Suite 1111-E 
> Baltimore, MD 21205 410-502-2619
> 
> 
> [[alternative HTML version deleted]]
> 
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