Hi Jim,
Is it correct that you measured every subject 100 times (25 times in all 4
drugs/dose groups)? Then it might be a good idea to use a repeated
measurement test. This tests takes into account that people may have a
different 'base' temperature; it takes away some of the within group error
and may give your test a greater power. It's easiest to use the mean of your
25 observations in the 4 groups, also because you don't seem to be
interested in differences in temperature over time or something.
Sky
Jim Kroger heeft geschreven in bericht ...
>Hello, I've received some expert help here on a couple previous occasions
>(thanks). I have an issue bothering me, which I'd like to present to you.
>
>I'm doing a two-way, 2X2 ANOVA. Suppose I have 20 subjects, and each has
>25 observations of the following types:
>
>drug1-doseA (25 for each subject)
>drug1-doseB ( " )
>drug2-doseA
>drug2-doseB
>
>Each observation consists of the subject's temperature. The objective is
>to determine whether there is a main effect of either factor (drug type
>and doseage) on temperature, and whether there is an interaction between
>the two.
>
>My question is, should I determine an average for each subject in each of
>the four cells, and use this as data to put into the ANOVA, or should I
>put the raw trials themselves into the ANOVA? There would be 80 datapoints
>and 2000 data points respectively, 20 or 500 per cell. I have seen both
>approaches taken but never heard a satisfactory justification. It would
>seem they are not equivalent since the latter, having more observations,
>has greater power. What are the implications of each option?
>
>Thank you much,
>Jim
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