I am not used to working with proc gen mode. It generates two sets of diagnostics of the residuals. One looks fine, the other may have a pattern in it. I don't know why I am getting two totally different sets of diagnostics, and which I should use. There are no comments other than what I show below.
proc gen mode diagnostics I don't understand.
- Thread starter noetsi
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I am not sure which one you mean, but do you know which is the correct set of diagnostics hlsmith. I can't figure this out at all.
This is payment, and we get a small number of people who earn huge amounts of money while most get very little. I tend to assume with 20 thousand cases one outlier won't matter much. Look at the DFBETA's this seems to be confirmed.
Which diagnostics do you look at in proc genmode for linear regression?
This is payment, and we get a small number of people who earn huge amounts of money while most get very little. I tend to assume with 20 thousand cases one outlier won't matter much. Look at the DFBETA's this seems to be confirmed.
Which diagnostics do you look at in proc genmode for linear regression?
Ok I have another question.
I am using PROC Genmode. 1 means you are in the group 0 you are not in the second column (please ignore the third column). I interpret this to mean that 16 -18 earn more than the excluded group which is 25-44 controlling for other variables. But that is hard to believe given what we know of our organizations and the descriptives. The code is really long so I did not include it. It is an interval response variable (income).
I am using PROC Genmode. 1 means you are in the group 0 you are not in the second column (please ignore the third column). I interpret this to mean that 16 -18 earn more than the excluded group which is 25-44 controlling for other variables. But that is hard to believe given what we know of our organizations and the descriptives. The code is really long so I did not include it. It is an interval response variable (income).
It is hard to ignore the third column! The indicators aren't clear given the above table. What I usually do is get the estimates from the model then make sure i can repeat them in the estimate statement, then tailor those to my question or reference groups of interest. It may help to show more of the output.
I have the whole population which is why I did not post the rest. In this case being 0 means you are not 16-18. So does this mean that if you are not 16-18 you earn 771 dollars more than the reference group and if you are 16-18 you earn 771 dollars less? That is a bit confusing to me. I don't understand why they score it by the 0 group relative to the reference category rather than the 1 (which means you are in the group) relative to the reference category.
Since I have a population I don't need a normal distribution, I don't even pay attention to p values. I don't know what an identity link is, I never heard of that. Do I need to test for non-linearity, the only assumption that matters I believe.
Genmod does not use reference coding. It uses GLM coding as the default. I really do not understand how that changes the interpretation.
Genmod does not use reference coding. It uses GLM coding as the default. I really do not understand how that changes the interpretation.
