David,
Thank you for your assistance. It did not occur to me use a corrected oneway anova after the repeated measures as I have always been taught that "contrasts" were the appropriate method (if used correctly!). The analysis now makes sense.
Jayne
----- Original Message ----
From: David Airey <[email protected]>
To: [email protected]
Sent: Tuesday, 24 June, 2008 9:02:57 PM
Subject: re: st: Re: Comparisons in repeated measures anova
.
Seems like you have one between sample factor (2 levels) and one
within sample factor (11 levels) and because you have an interaction,
you now want to test the simple effects, or the levels of system at
each time, or the levels of time within each system. For testing
different levels of the within sample factor (time) across the between
sample factor (system), you can just use a oneway ANOVA (or even ttest
since you have just two factor levels for system). You do have a
choice of errors for this test, one for just the time you are
interested in, or a pooled term, but I think most packages like SPSS
and SAS that automate this kind of ANOVA post estimation analysis (ie
give to you without asking) will use the MS at time k.
So, if you did
anova y a/s|a b a*b, repeated(b)
then if b = 1, 2, or 3, and a = 1 or 2
anova y a if b == 1
is fine, and applying a FWER as needed.
Also see the Stata FAQ of ANOVA.
> I am stuck with evaluation of a comparison. I have carried out a
> repeated measures anova of two systems (labeled 3 & 8) over 11 time
> periods, and I want to see if the two systems differ at each time
> period.
>
> . anova deltae sys / sample|sys time sys*time, repeated(time)
>
> Repeated variable: time
> Huynh-Feldt epsilon
> = 0.2594
> Greenhouse-Geisser epsilon
> = 0.1914
> Box's conservative epsilon
> = 0.1000
>
> ------------ Prob > F
> ------------
> Source | df F Regular H-F G-
> G Box
> -----------
> +----------------------------------------------------
> time | 10 20.30 0.0000 0.0000
> 0.0000 0.0011
> sys*time | 10 5.27 0.0000 0.0076
> 0.0160 0.0446
> Residual | 100
> -----------
> +----------------------------------------------------
> The design matrix has 48 columns and I tried to compare the systems
> at time 1 as follows:
> . test _coef[time[1]*sys[3]] = _coef[time[1]*sys[8]]
>
> ( 1) sys[3]*time[1] - sys[8]*time[1] = 0
>
> F( 1, 100) = 10.59
> Prob > F = 0.0016
>
> I interpret this as the 2 systems being significantly different. The
> problem I have is that the means of the two systems are 0.618 and
> 0.642. When the data is plotted there appears to be no difference at
> this time and a t-test (I appreciate that it is not valid in this
> design) has a probability 0.668 which seems to agree with the plot.
>
> I would be grateful if somebody could tell what I am doing wrong in
> this comparison and how to carry it out.
> Jayne
>
>
>
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