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AdityaKir
Fluorite | Level 6

Hello,

 

I am a bit confused about when to use proc reg and when to use proc glm. I want to find out the factors effecting Exists.

 

Below is my data table

 

BouncesExitsContinentSourcegroupTimeinpageUniquepageviewsVisitsBouncesNew
00OC(direct)18100
00N.America(direct)4100
00N.AmericaOthers35100
00N.Americapublic.tableausoftware.com70100
00N.Americapublic.tableausoftware.com81100
00N.Americapublic.tableausoftware.com75100
00N.Americapublic.tableausoftware.com186100
00N.America(direct)710100
00OC(direct)712110
00ASOthers344110
00EUOthers27110
00EUvisualisingdata.com0110
00N.AmericaOthers294110
00N.Americapublic.tableausoftware.com111110
00SA(direct)1430110
00N.America(direct)29110
00N.AmericaOthers637110
00N.Americagoogle10110
00N.Americagoogle42210

 

 

 

Thanks and regards,

 

Aditya

3 REPLIES 3
Reeza
Super User

What values does exits take on? 0/1?

 

PROC GLM does most of what PROC REG does. There was a comparison a short while ago here:

https://communities.sas.com/t5/SAS-Statistical-Procedures/HAS-PROC-REG-been-out-of-date/m-p/285418#M...

 

If your variable takes on the values 0/1 you shouldn't be using PROC REG - use PROC LOGISTIC or GLM. Since you have mostly categorical data, you can also do as already suggested by @Ksharp and use CATMOD.

Reeza
Super User

If you're new to SAS and statistics, the first SAS Statistics course, which covers regression and analysis is free here, bottom left corner. 

http://support.sas.com/training/tutorial/

Ksharp
Super User
proc reg only is suited for continuous variable.
proc glm can handle both continuous and category variables.

If EXISTS has only two value 0 and 1, then Logistic Regression (proc logistic , proc catmod .... )
or decision tree (proc hpsplit) is a good choice .


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