Hi, I'm currently working on an assignment in which I have to run a multiple regression, however I am a little confused regarding the order of the procedure.
I'll briefly outline the problem and what I have done so far:
The assignment deals with prediction of donating behaviour within a population. The predictors include age, gender, social integration, years of education, religion, and whether a serious life event has occurred in the person's life in the last 5 years such as illness of a family member.
So what I did was:
- Run a hierarchical regression with demographics such as age, gender and education in the first block and the other predictors in the second block.
- I found that the demographics were insignificant, the only significant predictors were religion and life event.
- Those were included in the final model.
I was wondering whether this is the correct course of action to take when doing a multiple regression? Along these lines, another question regards the procedure to follow with assumptions. For instance, I checked for outliers, and found one particularly large xy-outlier. When I removed it and reran the initial model, education became significant. When reporting this, can I disregard the initial model, in other words, could I have checked for assumptions on all the predictors, found outliers, removed them, and then used that as my final model?
Thanks in advance.
I'll briefly outline the problem and what I have done so far:
The assignment deals with prediction of donating behaviour within a population. The predictors include age, gender, social integration, years of education, religion, and whether a serious life event has occurred in the person's life in the last 5 years such as illness of a family member.
So what I did was:
- Run a hierarchical regression with demographics such as age, gender and education in the first block and the other predictors in the second block.
- I found that the demographics were insignificant, the only significant predictors were religion and life event.
- Those were included in the final model.
I was wondering whether this is the correct course of action to take when doing a multiple regression? Along these lines, another question regards the procedure to follow with assumptions. For instance, I checked for outliers, and found one particularly large xy-outlier. When I removed it and reran the initial model, education became significant. When reporting this, can I disregard the initial model, in other words, could I have checked for assumptions on all the predictors, found outliers, removed them, and then used that as my final model?
Thanks in advance.