Hi,
My data has 3 treatment groups each with results at 3 time points (baseline & 2 equally spaced follow-ups). I want to assess the effects of treatment group and time on the outcome. I use dataex to provide an example of my data structure below.
I have tried a few ways of doing this & would appreciate any advice on which is better/any preferences. Initially, to get a sense of the data, I tried simple t-tests comparing the results at each timepoint between treatment groups (2 at a time), and using paired tests to compare each visit to baseline by treatment group.
I would now like to use either a repeated measures anova or a mixed model to evaluate the effects. I use the following commands:
Do these codes seem appropriate? & is there a preference (statistical or other) over which to use?
Thank you for any help, Megan.
My data has 3 treatment groups each with results at 3 time points (baseline & 2 equally spaced follow-ups). I want to assess the effects of treatment group and time on the outcome. I use dataex to provide an example of my data structure below.
I have tried a few ways of doing this & would appreciate any advice on which is better/any preferences. Initially, to get a sense of the data, I tried simple t-tests comparing the results at each timepoint between treatment groups (2 at a time), and using paired tests to compare each visit to baseline by treatment group.
I would now like to use either a repeated measures anova or a mixed model to evaluate the effects. I use the following commands:
Code:
// ANOVA anova result group / id|group interval group#interval, repeated(interval) contrast interval@group, effect mcompare(bonferroni) anova result group##interval contrast group@interval, effect mcompare(bonferroni)
Code:
// MIXED mixed result group##interval || id:, var reml contrast group##interval contrast interval@group, effect mcompare(bonferroni) contrast group@interval, effect mcompare(bonferroni)
Thank you for any help, Megan.
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input long(group id) float interval double result 3 1 1 3.4 3 1 2 1.425 3 1 3 2.55 2 2 1 4.3 2 2 2 2.325 2 2 3 1.875 3 3 1 9.45 3 3 2 7.4 3 3 3 6.975 3 4 1 5.925 3 4 2 4.15 3 4 3 4.25 2 5 1 4.45 2 5 2 2.525 2 5 3 7.575 2 6 1 4.175 2 6 2 6.4 2 6 3 6.825 1 7 1 6.125 1 7 2 7.075 1 7 3 5.1 3 8 1 4.975 3 8 2 2.675 3 8 3 2.625 1 9 1 3.7 1 9 2 7.1 1 9 3 7.875 2 10 1 6.675 2 10 2 6.25 2 10 3 5.2 1 11 1 3.2 1 11 2 4.125 1 11 3 4.075 2 12 1 5.025 2 12 2 3.05 2 12 3 6.325 1 13 1 1.9 1 13 2 4.25 1 13 3 5.475 1 14 1 5.2 1 14 2 4.025 1 14 3 7.625 3 15 1 4.775 3 15 2 4.9 3 15 3 4.45 1 16 1 2.325 1 16 2 5 1 16 3 6.175 1 17 1 5.05 end label values group group label values id id
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