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sasCommunity Tip of the Day
Autocorrelation of the error function is something that needs to be addressed in linear regression. If strong autocorrelation exists, then autoregressive models will be more appropriate as opposed to linear regression for the independence assumption of linear regression is severely violated. If no such strong autocorrelation exist, for beginnners, we have no additional reasons to reject linear regression model as a suitable model.
To test for serial autocorrelation in linear regression, one should use the DW option in PROC REG.
PROC REG; MODEL Y = X/DW; RUN;QUIT;
It should be noted that the Durbin-Watson statistics are not relevant in certain scenarios where normality assumptions are violated or when variables which are extremely time-dependent (lag variables) are used. In these cases, the more relevant serial correlation test which is the Breusch-Godfrey test will be more relevant.
Submitted by Murphy Choy. Contact me at my Discussion Page.
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2017 Green Thumb Award Announced
May 2, 2017
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Scholarships Available for Regional Conferences
May 8, 2017
Conference scholarships and grants for students, faculty and professionals
Calling all students, faculty and professionals who are users of SAS®! Did you know scholarships and grants are available to attend the regional users conferences? Check out the benefits of applying, and don’t miss out on these opportunities! Scholarship and grant benefits can include but are not limited to:
- Reduced or waived registration fee.
- Travel stipend.
- Free or reduced lodging.
- And more!
Student scholarships are available to full-time, degree-seeking college students using SAS in their coursework or research. Note the application deadlines below:
- Apply by June 19 to attend WUSS
- Apply by June 30 to attend MWSUG
- Apply by Aug. 5 to attend SCSUG
- Apply by July 3 to attend SESUG
Professional scholarships are available to full-time professionals who have been using SAS for three years or less in daily work. Note the application deadlines below:
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