How to calculate adjusted odds ratios using weighted logistic regression analysis?

[Momo Ito]

I am a master's student working on a cross-sectional analysis of a large database.

Using one binary variable as the dependent variable and up to 10 categorical variables as independent variables, I am investigating the factors that are most strongly associated with the outcome.

Therefore, I would like to perform a logistic regression analysis of the independent variables and dependent variables before and after adjusting the covariates (background factors of the subjects).

This is where the problem arises.

As far as I've researched, the code seems to be written so that the moderators are aligned with the independent variables during analysis, but is this correct?
Ex.　logistic <depvar> i.independentvar <covariatesvar>

If so, are covariates treated as independent variables?

I want to solve this because if they are treated as independent variables, it will exceed the desired number of variables to be input.

The maximum number of variables in a logistic regression analysis is said to be N/10. Still, the maximum number that can be input is 10, which are currently independent variables, for the data I am working with.

There are 8 variables treated as covariates related to the dependent variable. I plan to eliminate non-significant results from the bivariate analysis, so the number may be reduced.

I apologise for bothering you during your busy schedule, but I would appreciate your response.

[George Ford]

N/10 is a rule of thumb for the number of observation needed per regressor. This would suggest you have a sample size of 100 (100/10 = 10). That is not a large database.

Covariates are not moderators. Moderators have a specific meaning. Look it up so you know.

You appear to be running a basic logistic regression. If you have a large sample, then proceed.

DO NOT exclude variables based on t-test from bivariate regression (for several reasons). Include all variables you think are theoretically relevant.

I see nothing about odds ratio and weighting in your post.