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.