[R-sig-ME] longitudinal with 2 time points

[Charles E. (Ted) Wright]

Keep in mind that running an ANOVA on the difference is not the same thing 
as using the baseline data as a covariate in an ANOVA on the Week 4 data. 
Essentially the ANOVA on the differences is like the ANCOVA with the slope 
constrained to be 1.

Ted Wright

On Wed, 11 Aug 2010, John Maindonald wrote:

> All these are possibilities, except maybe making baseline measurement
> a random factor.  This would make sense only if data divide into groups,
> and you want the baseline effect to vary randomly from group to group.
> That may limit your ability to estimate parameters that are of interest.
> In most circumstances that I am familiar with, it makes better sense to
> treat baseline effect as fixed.
>
> John.
>
> John Maindonald             email: john.maindonald at anu.edu.au
> phone : +61 2 (6125)3473    fax  : +61 2(6125)5549
> Centre for Mathematics & Its Applications, Room 1194,
> John Dedman Mathematical Sciences Building (Building 27)
> Australian National University, Canberra ACT 0200.
> http://www.maths.anu.edu.au/~johnm
>
> On 11/08/2010, at 8:11 AM, array chip wrote:
>
>> Hi, I am wondering if it is still meaningful to run a mixed model if a
>> longitudinal dataset has only 2 time points (baseline and week 4)? Would it be
>> more appropriate to simply take the difference between the 2 time points and run
>> ANOVA (ANCOVA) on the difference? what about still running mixed model on the
>> difference of the 2 time points, but adding baseline measurement as a random
>> factor?
>>
>> Thanks for sharing your thoughts.
>>
>> John
>>
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