Yous could (should?) use an anaysis of covariance, i.e. a regression:

post = pre + group (in that order)

Yes, you can use repeated measures ANOVA for 2 samples with 2 time points. Repeated measures ANOVA is a statistical technique used to analyze data when:

- You have multiple measurements from the same subjects (e.g., two time points)

- You want to compare means between groups (e.g., two samples)

- You want to account for the correlation between repeated measurements

In your case, you have:

- 2 samples (e.g., treatment and control)

- 2 time points (e.g., pre-treatment and post-treatment)

Repeated measures ANOVA can help you:

- Compare means between the two samples at each time point

- Examine the effect of time (change from pre to post) within each sample

- Investigate the interaction between sample and time (e.g., whether the change from pre to post differs between samples)

Just ensure that your data meets the assumptions of repeated measures ANOVA, such as normality, sphericity, and no significant outliers.

Aisha Ejura Dahunsi please stop spamming AI generated answers, without mentioning it! Besides that, the AI generated answer is wrong, at best misleading!!! So, please at least understand yourself what you are posting.

Ali Itimad There are several methods to analyze the data and all have their pros and cons. Just to give you some examples:

1) If you really have a randomized controlled trial and true random allocation to the groups, then both groups should not differ at the first measurement (thats the point of random allocation). Therefore, you could simply compare the groups at post treatment.

2) You could use an ANOVA approach, but then you need a 2 factorial ANOVA, with repeated measures on one factor, i.e. a 2 (group) X 2 (time) ANOVA with rm on the second factor, sometimes calle split-plot design. Your effect of interest would be, if the interaction shows an effect, i.e. if the changes from t1 to t2 are different for the 2 groups.

3) You could calculate the difference t2-t1 for all participants and conduct a between sample t-test with groups as independent variable. The result is identical to the interaction of the ANOVA approach mentioned before, but you loose all other information. But if you are only interested in the difference in slopes, then you could do this.

4) You could follow Jos Feys advice and use an ANCOVA approach, where you have the between factor group, but you account for the repeated measures by incorporating t1 as covariable. The interpretation is slightly different, but also valid and it has typically more power than the 2factorial ANOVA.

5) Another approch would be to use a multilevel model. Here you would formulate the model similar to the 2factorial model, but you would account for the repeated measures with the random effect for the participants. Now you could get fancy and incorporate also random slopes, if you go Bayesian (otherwise there is not enough information to calculate the model in the typical frequentist realm).

As you can see, there are plenty of options and this is not exhaustive. Nowadays, it is typically recommended to use the multilevel approach, but with 2 time points and 2 groups, under normal conditions, this should not differ much (if at all for some parametrizations) to the ANOVA approach.

Hello Ali Itimad. Assuming you randomly allocated Ss to your two groups, I agree with Jos Feys. Here is an article you may find helpful if you have to explain why ANCOVA is appropriate for your design:

Article Statistics Notes: Analysing controlled trials with baseline ...

PS- Rainer Duesing, I do not disagree with anything you said. But I do think that ANCOVA is a nice and very defensible method here, if there is random allocation to groups. ;-)

Repeated measures ANOVA is typically used when you have three or more measurements on the same experimental unit. In the case of two samples with two time points each, you may not be able to use a traditional repeated measures ANOVA because you don't have enough time points to analyze the within-subjects effects.

However, you can still compare the means of the two samples at two time points using a paired t-test or a two-way ANOVA. The paired t-test would compare the means of the two samples at each time point separately, while the two-way ANOVA would allow you to test the main effects of the two samples and the time points, as well as their interaction effect.

So, in summary, for two samples with two time points each, you can use a paired t-test or a two-way ANOVA, but not a traditional repeated measures ANOVA.

Dilshad Altalabani, suppose I had baseline and followup scores for just one group. Would you advise me to avoid using a one-factor repeated measures ANOVA in that case too? Thank you for clarifying your position.

Yes, I would advise against using a one-factor repeated measures ANOVA (also known as a within-subjects ANOVA) with only one group and two time points (baseline and follow-up).

Reason is because:

1. Repeated measures ANOVA assumes multiple groups or conditions, which is not the case here.

2. With only one group, you don't have a control group to compare the changes to.

3. The analysis would essentially become a paired t-test (or dependent t-test), which is a more appropriate choice for this design.

Using a repeated measures ANOVA in this scenario might lead to:

- Inaccurate degrees of freedom

- Incorrect F-statistic calculations

- Inflated p-values

Instead, use a paired t-test (or dependent t-test) to compare the mean differences between the baseline and follow-up scores within the single group. This will provide a more appropriate and valid analysis for your data.

Let me know if you have any further questions or concerns. Thank you

Aisha Ejura Dahunsi do you even read the bullsh*t you copied from an AI chatbot answer?

Dr. Rainer Duesing, I appreciate your feedback and acknowledge my oversight in not properly attributing AI-generated responses. I will ensure that I accurately cite the sources of my information going forward. Thank you for bringing this to my attention and for helping me improve my practices.

Aisha Ejura Dahunsi wrote:

1. Repeated measures ANOVA assumes multiple groups or conditions, which is not the case here.

A one-factor repeated measures (RM) ANOVA assumes that there are k = 2 or more measurements of the DV for each independent subject. When k = 2, the F-test from a one-factor RM ANOVA is equivalent to a paired t-test, t2 = F. (Try it if you don't believe it!)

The design Ali Itimad described has k = 2 measurements of the DV for each independent subject, but it also has two independent groups of subjects (control & intervention). One option for that design is what I would call a 2x2 mixed design ANOVA*, with Group as a between-Ss factor and Time (pre, post) as a within-Ss (or repeated measures) factor. But another option is ANCOVA, as suggested by Jos Feys (and seconded by me).

* I know that some folks (and maybe some disciplines) refer to any ANOVA model that has at least one RM factor as a repeated measures ANOVA. This is a very imprecise description that can cause a lot of confusion, IMO. I think it is wise to spell out explicitly how many factors there are, including which factors are between-Ss factors and which ones are within-Ss factors. YMMV.

PS- Thank you for acknowledging your oversight in not citing the source of the material you posted earlier. As I have said in other threads, I firmly believe that posting AI-generated content without proper attribution is just another form of academic dishonesty. And I wish people would stop doing it!

Seconding and amplifying bruces sentiment on AI solutions pasted here. If i want robot answers to questions ill use chat gpt directly. Looking for actual, not artificial onteligence on this site.