BookmarkSubscribeRSS Feed
Sathish_jammy
Lapis Lazuli | Level 10

Dear Experts,

 

I have trouble in finding the confidence interval value for the attached (CSV) data. Please have a look at the attachment.

The data contains 2 variables Grade (1 / 0) - dependent variable, WeightHeightRatio value(Independent variable).

While evaluating an odd-ratio for the data I get a result as kind of infinity. ---->999.999 ????????

 

Odds Ratio Estimates and Profile-LikelihoodConfidence Intervals

 

EffectUnitEstimate95% Confidence Limits
WHtR1440.66672.929>999.999

 

proc logistic data = reg2 plots=roc;
model Grade1(event='1') = WHtR;
roc 'WHR' WHtR;
run;

/*I tried a alternate way to ommit the infinity value*/
proc logistic data = reg2 plots=roc;
model Grade1(event='1') = WHtR / FIRTH clodds = pl;
roc 'WHR' WHtR;
run;
/*But get the same result*/

I attach my dataset as well here. Please let me know where I went wrong.

Thanks in advance!

 

 

3 REPLIES 3
Rick_SAS
SAS Super FREQ

You have not necessarily done anything wrong. The estiamte for odss ration is EXP(b1), where b1=6.1056 is the estimate for the WHtR variable. The lower/upper limits are 

exp(b1 +/- 1.96*StdErr), which is

72.784571
2761.9604

 

For a discussion and example, see the end of the article "Formats for p-values and odds ratios in SAS."

Sathish_jammy
Lapis Lazuli | Level 10

Dear @Rick_SAS 

 

Thank you so much for your suggestion.

But it looks like weird to get a very big odds ratio in this logistic regression.

Do you think, Is it fine to considerable to present in the report?

 

Even though I followed a few procedures to get exact results.

1. Removing Outliers
2. Amount of Missing Values and handle the missing values
 
but still, the odds ratio is huge.
 
Odds Ratio Estimates
Effect Point Estimate 95% WaldConfidence LimitsWHtR
448.34872.779>999.999

 

Analysis of Maximum Likelihood Estimates
Parameter DF Estimate StandardError WaldChi-Square Pr > ChiSqInterceptWHtR
1-1.51590.53018.17770.0042
16.10560.927643.3206<.0001
 

As per your statement : 

The estimate for odds ratio is EXP(b1), where b1=6.1056 is the estimate for the WHtR variable. The lower/upper limits are 

exp(b1 +/- 1.96*StdErr), which is

72.784571
2761.9604

 

Can I present an Odds Ratio as 448.348 (95%CI 72.78 - 2761.96) ...

 

Rick_SAS
SAS Super FREQ

> Do you think, Is it fine to considerable to present in the report?

 

You should discuss this issue with your colleagues or supervisor.

.

>  Can I present an Odds Ratio as 448.348 (95%CI 72.78 - 2761.96) 

 

Yes, you could do that. If you use four significant digits, it would be (72.78, 2762).

SAS INNOVATE 2024

Innovate_SAS_Blue.png

Registration is open! SAS is returning to Vegas for an AI and analytics experience like no other! Whether you're an executive, manager, end user or SAS partner, SAS Innovate is designed for everyone on your team. Register for just $495 by 12/31/2023.

If you are interested in speaking, there is still time to submit a session idea. More details are posted on the website. 

Register now!

What is Bayesian Analysis?

Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.

Find more tutorials on the SAS Users YouTube channel.

Get the $99 certification deal.jpg

 

 

Back in the Classroom!

Select SAS Training centers are offering in-person courses. View upcoming courses for:

View all other training opportunities.

Discussion stats
  • 3 replies
  • 3467 views
  • 1 like
  • 2 in conversation