turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

Find a Community

- Home
- /
- Analytics
- /
- Stat Procs
- /
- null model fit statistics using PROC LOGISTIC and ...

Topic Options

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Highlight
- Email to a Friend
- Report Inappropriate Content

09-30-2009 11:31 AM

Dear all,

I want to get -2LogL of the null model using proc logistic. I thought there are two ways to do that.

1) Run the model without specifying any independent variable, i.e.

proc logistic data = mydata descending;model youtcome = /firth;run;

In the output, I found:

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

-2 Log L = 38.858

2) Run the model by specifying independent variables, and use the model fit

statistics in the Intercept Only column. For example:

proc logistic data = mydata descending; model youtcome = weight/firth; run;

In the output, I found:

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

Model Fit Statistics

Criterion Intercept Only Intercept and Covariates

AIC 31.570 31.805

SC 33.790 36.244

-2 Log L 29.570 27.805

Why the -2LogL in the Intercept Only column (29.570) is different from what I got from the first method (38.858)? And if I specify different independent variables, the model fit statistics in the Intercept Only column also vary. So what does "Intercept Only" mean? And which one is the correct null model fit statistics?

If I turn off the "Firth" option, the two null model fit statistics (-2logL) are the same. But the problem is that my data has quasi-complete problem and "Firth" should give me more reliable results.

Thanks!

koko

I want to get -2LogL of the null model using proc logistic. I thought there are two ways to do that.

1) Run the model without specifying any independent variable, i.e.

proc logistic data = mydata descending;model youtcome = /firth;run;

In the output, I found:

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

-2 Log L = 38.858

2) Run the model by specifying independent variables, and use the model fit

statistics in the Intercept Only column. For example:

proc logistic data = mydata descending; model youtcome = weight/firth; run;

In the output, I found:

Model Convergence Status

Convergence criterion (GCONV=1E-8) satisfied.

Model Fit Statistics

Criterion Intercept Only Intercept and Covariates

AIC 31.570 31.805

SC 33.790 36.244

-2 Log L 29.570 27.805

Why the -2LogL in the Intercept Only column (29.570) is different from what I got from the first method (38.858)? And if I specify different independent variables, the model fit statistics in the Intercept Only column also vary. So what does "Intercept Only" mean? And which one is the correct null model fit statistics?

If I turn off the "Firth" option, the two null model fit statistics (-2logL) are the same. But the problem is that my data has quasi-complete problem and "Firth" should give me more reliable results.

Thanks!

koko