BookmarkSubscribeRSS Feed
☑ This topic is solved. Need further help from the community? Please sign in and ask a new question.
jim_wong
Calcite | Level 5

Hi Everyone,

 

I am a new user, currently completing panel regression analysis for a university paper. The data I am using is a sample taken from the US Panel Study of Income Dynamics (PSID), with 23 variables and ~220k observations.

 

When I run a simple panel model, such as below, I do not get the observation plots, and the colored set of residual plots seem incomprehensible. Is it simply a case of so many observations making the plots over-complicated? Are these plots "normal" for proc panel, and if so how do I interpret them?

 

Thank you for any advice.

 

proc panel data=data plots=ALL;
id year id;
model ARSINH_wealth = pd age male white black hispanic otherrace education income employed divorce
marriage childbirth familydeath laidoff missedwork studentloan collegedegree ARSINH_socioeconomic / pooled;
title 'Model One - Pooled (OLS) Model (negative)';
run;

 

jim_wong_0-1652942236726.jpeg jim_wong_1-1652942247355.jpeg

 

This question was originally posted to 'New Users' but I was advised to post it here instead.

1 ACCEPTED SOLUTION

Accepted Solutions
acordes
Rhodochrosite | Level 12

Perhaps the visuals get more meaning if you work with a sample of the data. 

You could try subsetting your data. 

 

data want;
set data;
sample_filter=rand("integer", 1, 20);
run;

proc panel data=want plots=ALL;
where sample_filter = 1;   /* in this case you would work with a sample rate of 5% */ 
id year id;
model wealth = pd age male white black hispanic otherrace education income employed divorce
marriage childbirth familydeath laidoff missedwork studentloan collegedegree ARSINH_socioeconomic / pooled;
title 'Model One - Pooled (OLS) Model (negative)';
run;

 

View solution in original post

6 REPLIES 6
jim_wong
Calcite | Level 5

Hi Everyone,

 

I am a new user, currently completing panel regression analysis for a university paper. The data I am using is a sample taken from the US Panel Study of Income Dynamics (PSID), with 23 variables and ~220k observations.

 

When I run a simple panel model, such as below, I do not get the observation plots, and the colored set of residual plots seem incomprehensible. Is it simply a case of so many observations making the plots over-complicated? Are these plots "normal" for proc panel, and if so how do I interpret them?

 

Thank you for any advice.

 

proc panel data=data plots=ALL;
id year id;
model wealth = pd age male white black hispanic otherrace education income employed divorce
marriage childbirth familydeath laidoff missedwork studentloan collegedegree ARSINH_socioeconomic / pooled;
title 'Model One - Pooled (OLS) Model (negative)';
run;

 

jim_wong_1-1652906237704.jpeg jim_wong_0-1652906184544.jpeg

 

sbxkoenk
SAS Super FREQ

Hello @jim_wong ,

 

@SASCom1 can help you with this.

 

Thanks,

Koen

acordes
Rhodochrosite | Level 12

Perhaps the visuals get more meaning if you work with a sample of the data. 

You could try subsetting your data. 

 

data want;
set data;
sample_filter=rand("integer", 1, 20);
run;

proc panel data=want plots=ALL;
where sample_filter = 1;   /* in this case you would work with a sample rate of 5% */ 
id year id;
model wealth = pd age male white black hispanic otherrace education income employed divorce
marriage childbirth familydeath laidoff missedwork studentloan collegedegree ARSINH_socioeconomic / pooled;
title 'Model One - Pooled (OLS) Model (negative)';
run;

 

sas-innovate-2024.png

Available on demand!

Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.

 

Register now!

Multiple Linear Regression in SAS

Learn how to run multiple linear regression models with and without interactions, presented by SAS user Alex Chaplin.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 6 replies
  • 2871 views
  • 1 like
  • 5 in conversation