[R] Missing data and LME models and diagnostic plots

[Mark Difford]

Peter Flom wrote:

>> I am puzzled by the performance of LME in situations where there are
>> missing data.  As I 
>> understand it, one of the strengths of this sort of model is how well it
>> deals with missing 
>> data, yet lme requires nonmissing data. 

You are confusing missing data with an unbalanced design. A strengths of LME
is that it copes with the latter, which aov() does not.

Regards, Mark.


Peter Flom-2 wrote:
> 
> Hello
> 
> Running R2.9.2 on Windows XP
> 
> I am puzzled by the performance of LME in situations where there are
> missing data.  As I understand it, one of the strengths of this sort of
> model is how well it deals with missing data, yet lme requires nonmissing
> data.  
> 
> Thus, 
> 
> m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_,
>                 data = long,
>                 random = ~I(year-2007.5)|schoolnum)
> 
> causes an error in na.fail.default, but adding na.action = "na.omit" makes
> a model with no errors.  However, if I create that model, i.e.
> 
> m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_,
>                data = long, 
>                random = ~I(year-2007.5)|schoolnum,
>                na.action = "na.omit")
> 
> then the diagnostic plots suggested in Pinheiro & Bates produce errors;
> e.g.
> 
> plot(m1.mod1, schoolnum~resid(.), abline = 0)
> 
> gives an error "could not find function "NaAct".
> 
> 
> Searching the archives showed a similar question from 2007, but did not
> show any responses.
> 
> Thanks for any help
> 
> Peter
> 
> )
> 
> Peter L. Flom, PhD
> Statistical Consultant
> Website: www DOT peterflomconsulting DOT com
> Writing; http://www.associatedcontent.com/user/582880/peter_flom.html
> Twitter:   @peterflom
> 
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> 

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