Hello,
My dataset is in the following format
Year Exposure Outcome
2001 10 35
2002 23 45
2003 12 78
2004 17 70
2005 27 80
2006 59 100
2007 39 190
2008 20 391
2009 60 192
2010 10 53
Both Exposure and Outcome are continuous variables. I have constructed a simple linear regression model with Exposure as the independent variable and Outcome as the dependent variable.
Based on the results of the linear regression, I have manually generated predicted values of the Outcome for given exposure values with 2-year lag period (e.g. prediction for 2003 based on 2001 exposure). How can I automate this process in SAS because I need the corresponding 95% confidence intervals for the predicted values?
Thank you.
Hello,
My dataset is in the following format
Year Exposure Outcome
2001 10 35
2002 23 45
2003 12 78
2004 17 70
2005 27 80
2006 59 100
2007 39 190
2008 20 391
2009 60 192
2010 10 53
Both Exposure and Outcome are continuous variables. I have constructed a simple linear regression model with Exposure as the independent variable and Outcome as the dependent variable.
Based on the results of the linear regression, I have manually generated predicted values of the Outcome for given exposure values with 2-year lag period (e.g. prediction for 2003 based on 2001 exposure). How can I automate this process in SAS because I need the corresponding 95% confidence intervals for the predicted values?
Thank you.
The simple linear regression can be done like this
data have;
input Year Exposure Outcome;
datalines;
2001 10 35
2002 23 45
2003 12 78
2004 17 70
2005 27 80
2006 59 100
2007 39 190
2008 20 391
2009 60 192
2010 10 53
;
proc reg data = have;
model Outcome = Exposure / cli clm;;
run;
Though I am not sure what you are askeing regardring lagging values? Do you want to lag values of outcome before of after the regression analysis?
Thank you for your response.
The abovementioned code gives a regression equation as follows,
Outcome = Constant + Beta*Exposure
Outcome = 83.23453 + 1.45002*Exposure
If I want to predict Outcome for 2005, then it would be 122.4 (83.23453 + 1.45002*(27)). However, if I lag the exposure by 2-year period, then it would be 100.6 (83.23453+ 1.45002*(12)). SAS does the former automatically, but I need to automate the latter because I need the corresponding confidence intervals for the predicted values based on 2-year exposure lag. I hope this clarified the question.
What you're asking for is called scoring a dataset. There are multiple options to do so which are illustrated here:
http://blogs.sas.com/content/iml/2014/02/19/scoring-a-regression-model-in-sas.html
You will need to lag the data yourself though because you're using a REG model, if you were using a Time Series Proc it may be more automated.
FYI @ImSame & @PeterClemmensen I've merged the two threads into one.
EDIT: three threads...
Please do not cross post, most of the users in here are on multiple communities, so stick to the statistical procedures community for this one 🙂
Sorry I am new here, I'll continue posting on that thread. Thanks!
No Problem 🙂
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