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If there are two groups (IV: treatment / no treatment) with say 15 participants each, and for each participant the same observer has completed a questionnaire (DV: outcome measure, completed once for each participant by the same observer; interval scale), what kind of data analysis would be appropriate? I am interested if participants in the two groups differ on the outcome measure, which has been completed by the same observer for all participants.

For a dependent t-test, data structure would look like this

group 1 (control group): 2, 4, 3, 2, 2, 5, 3, 2, 3 etc.

group 2 (treatment group): 3, 2, 4, 4, 1, 2, 3, 1, 1 etc.

but I feel this would not make sense as it is not a pairing within the "participants" (for each participant, there is only one score); all data is provided by the same observer.

Also, as a second step: What approach could be used for two groups with 30 "participants" each where observer A contributes 15 values per group and observer B also 15 values per group?

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  • $\begingroup$ You stress that both groups have same 'observer"? What do you mean by 'observer' and you do you mention there is only one? $\endgroup$
    – BruceET
    Jul 28, 2020 at 17:02

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This kind of sounds like a repeated measures experiment, where a group undergoes testing, and then they repeat that same test under a single different condition (in your case a later time).

A little more info would be helpful, like what are your dependent and independent variables, are you testing the observer, or the participants? From my current understanding of your question, a paired samples T-test would probably be the way to go, if you are comparing means.

As for your second part, i would run a 2x2 anova to properly analyze that. you have group A doing task 1, and task 2. You then have group B doing task 1, and task 2. this would be best comapred using a repeated measures anova, with the post-hoc test of your choosing.

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  • $\begingroup$ Thanks for your response. I have edited the original post and added some more information. I was thinking of a dependent t-test too, but I would not know how to enter the data in a meaningful way, as there are no paired datasets as there usually are with a dependent t-test. $\endgroup$
    – grey
    Jul 28, 2020 at 13:05
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    $\begingroup$ thank you for the clarity. I think the best way to go about this would be to use the 2 groups and compare with a t-test as you normally would. it doesn't really matter that there was 1 person observing (it might actually be better as it rules out a third variable problem), as long as his observations remained impartial throughout. so I would say to run the test as you would like any dependent t-test. I have also added a little more about your second step in my answer $\endgroup$
    – user292603
    Jul 28, 2020 at 13:10

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