Hi CS,

I did these calculations utilizing equations on Excel so whatever TTEST variant is used there is what I used.
Even excel has the test type:
TTEST(

*array1*,

*array2*,

*tails*,

*type*)

1 – Paired

2 – Two-sample equal variance (homoscedastic)

3 – Two-sample unequal variance (heteroscedastic)

I guess it is 2 different tests but unsure what this means for our data.
Generally, when you are doing several tests in each test you have the option to get incorrectly a significant result (type I error)
If you do several tests the probability to get a false positive is higher, especially if the tests are independent.

Some people correct the significance level to reduce such a problem (for example Bonferroni correction, overcorrection ..)

Several questions but most questions ask for a number 1-10. Below are the links to the score forms if you're curious. The AOFAS score form has specific questions pertaining to pain and function and some subjective information that was also filled out but not by the patients.
https://orthotoolkit.com/aofas-ankle-hindfoot/

https://orthotoolkit.com/ffi/

Visual Analog Scale (VAS)
Do you know to define

**now **what "difference" do you want to identify?

If you don't have a clue you can always just take a medium standardized effect size (0.5)

I am unsure what you're asking based on the wording of your question, sorry.
If you want to be able to identify the "difference" of 2, for example, Group1: 7.5 and group2 9.5, you may need a small sample size.

but if the difference will be smaller than 2 you may not get a significant result, and this will not prove that there is no difference between the groups ...

If you want to identify a small difference like 0.2, for example, 7.5 and 7.7, you may need a larger sample size.

You may use the following to calculate the

**priori **test power (generally you should do before the experiment)

https://www.statskingdom.com/30test_power_all.html or GPower application.

I did click on the link and I am not sure which calculator to use as none say "priori".
Priori only say that you do the calculation before the experiment, and based on the expected difference, not the actual difference.(post-hoc)

I believe we should use only the prior test power.

You can't do it before, but you can do it based on the expected difference.

So it is the same calculation, but the question is what is your input data,

https://www.statskingdom.com/32test_power_t_z.html (choose "T" distribution,"two samples