# Recent content by Omerikooo

1. ### Interaction in linear regression

I don't understand why not ? You can use BMI as a continuous variable and introduce an interaction variable with age group. For example Y = Intercept + Beta1*BMI +Beta2*BMI*(Age Category = Adolescents) + Beta3*BMI*(Age Category = Adult) This model would adjust BMI coefficient according to age...
2. ### Interaction in linear regression

Okay. If you are okay with it no problem.
3. ### Interaction in linear regression

Hello, I can help you about the interpretation but why do you include both obese and overweight at the same time. Couldn't you use only one variable including reference, overweight and obese. This would make better sense. For a female obese: Y = 4.4004 + 0.041*ethnicity - 0.071*age -...
4. ### Comparing two groups with categorical data- Need help in choosing the correct stat test to assess significance

Okay, I'm not sure what that really means. Odds ratio can be calculated from contingency tables as you put in the second photo. But I'm also sure that it can be calculated via logistic regression analysis. There should be a relationship between them but I don't know really. I will try to do...
5. ### Comparing two groups with categorical data- Need help in choosing the correct stat test to assess significance

To give odds you should do logistic regression. With chi or fisher you can only report significant frequency difference between groups with regards to your findings. Chi and fisher doesn't give Odds.
6. ### Comparing two groups with categorical data- Need help in choosing the correct stat test to assess significance

Yes I mean a chi-square test for every finding. To run a Chi-square test your data is adequate. Expected values are intrinsically calculated in chi-square formula based on your contingency table, so no, you don't need to provide extra expected characteristics data, chi-square test takes care of...
7. ### Comparing two groups with categorical data- Need help in choosing the correct stat test to assess significance

Hello, I think you should do repeated Chi-square tests (fisher if needed) for each outcome. For example fining A present/absent vs controls/cases. This will simply show if the frequency of your findings differ between cases and controls. BUT! I wouldn't stop there. Seeing the predictive value...
8. ### binomial problem

Hey, Question asks the possibility of tossing the dice two times before tossing blue, in other words it asks. 1(all possible tosses) - the possibility of tossing the dice blue before the third toss. In this case there are 2 possibilities. You can toss the dice blue first and stop, the second...
9. ### Failure to calculate Kappa for a constant rater.

This article by Hripcsak and Heitjanb tackles many issues I came up to when doing work about reliability analyses is good help. It also includes tetrachoric correlation discussion as well. https://core.ac.uk/download/pdf/82193386.pdf
10. ### Failure to calculate Kappa for a constant rater.

I think tetrachoric correlation may be a solution for me.