Contributor
Posts: 33

Significance of Chi -Square Statistics in MLE in Proc Logistic

Hi,

In Proc Logistics , Maximum Likelihood Estimate is received as an output. For each variable , estimate , Standard Error & Chi-Square statistics is obtained. Estimate =  Chi-Square statistics / Standard Error.

My question is Chi Square distribution is the distribution of frequencies , so how can it  be used in above formula. The formula very well suits , when we calculate estimate from t-statistics in Linear Regression. T- Statistics follows T distribution which is (x- u)/ SE.

How the same fornmula can be used for Logistic and Linear regression is something not clear to me.

Thanks,

Vishal

SAS Super FREQ
Posts: 3,839

Re: Significance of Chi -Square Statistics in MLE in Proc Logistic

Sorry if I am misunderstanding, but I cannot reproduce your assertion that "Estimate =  Chi-Square statistics / Standard Error".  Could you show us what code you are using (and data, if possible)?

Here is an example from the Getting Started example in the PROC LOGISTIC documentation. In this example, the product of the Estimate column and the Standard Error column does not equal the Wald Chi-Square column.

data ingots;
input Heat Soak NotReady Freq @@;
datalines;
7 1.0 0 10  14 1.0 0 31  14 4.0 0 19  27 2.2 0 21  51 1.0 1  3
7 1.7 0 17  14 1.7 0 43  27 1.0 1  1  27 2.8 1  1  51 1.0 0 10
7 2.2 0  7  14 2.2 1  2  27 1.0 0 55  27 2.8 0 21  51 1.7 0  1
7 2.8 0 12  14 2.2 0 31  27 1.7 1  4  27 4.0 1  1  51 2.2 0  1
7 4.0 0  9  14 2.8 0 31  27 1.7 0 40  27 4.0 0 15  51 4.0 0  1
;

ods select ParameterEstimates;
proc logistic data=ingots;
freq Freq;
run;
Super User
Posts: 20,735

Re: Significance of Chi -Square Statistics in MLE in Proc Logistic

I think your question is statistical, not really related to SAS. You can review the statistical methods behind logistic regression here:
http://www.upa.pdx.edu/IOA/newsom/da2/ho_logistic.pdf

Or in a variety of other places.
Valued Guide
Posts: 684