nielsen...@gmail.com

2020-10-16 13:30:36 UTC

Hii,

I have a question about whether or not including a significant interaction between background variable (SES) and predictor (Years in firm).

I have 2 background variables: Gender and SES. My main predictor is years in firm, and my outcome variable is whether people do or do not prefer to cooperate with colleagues. I am trying to build a logistic regression model.

I first built the following model.

block 1: Gender & SES. I included this in the first block as I wanted to correct for those background variables.

block 2: Years.

However, I found that the interaction term SES*Years is significant. So should I include it in my final model or should I leave my model as described above.

I have a question about whether or not including a significant interaction between background variable (SES) and predictor (Years in firm).

I have 2 background variables: Gender and SES. My main predictor is years in firm, and my outcome variable is whether people do or do not prefer to cooperate with colleagues. I am trying to build a logistic regression model.

I first built the following model.

block 1: Gender & SES. I included this in the first block as I wanted to correct for those background variables.

block 2: Years.

However, I found that the interaction term SES*Years is significant. So should I include it in my final model or should I leave my model as described above.