1. Testing Significance of coefficients Usually, first examination of model Does the model including the independent variable provide significantly more information than a model without the variable?

2. Compare two models Model containing x Null (Intercept only model)

3. The null (intercept only) model proc freq data=s5238.chdage; tables chd; run; proc logistic data=s5238.chdage descending; model chd=; run;

4. Simple Linear Regression title "Height and FEV in 12 boys, 10-15 years old"; data fev1ht; input height fev @@; label fev="Forced Expiratory Volume (liters)" height="Height (cm)"; datalines; 134 1.7 158 2.7 138 1.9 162 3.0 150 2.2 174 3.8 142 2.0 166 3.1 146 2.1 170 3.4 154 2.5 178 3.9 ; proc sql; select * from fev1ht order by height ; quit; title;

5. Simple linear regression, proc reg proc reg data=fev1ht plots=none; model fev=height; quit;

6. Two Equivalent Tests

7. Two tests (no longer equivalent -- asymptotically equivalent) Wald Test Likelihood Ratio Test

8. Wald Test (two equivalent versions)

9. ods select parameterestimates; proc logistic data=s5238.chdage descending; model chd=age; run;

10. The Likelihood Ratio Statistic Software usually report either log(likelihood) or -2log(Likelihood) SAS reports -2log(Likelihood) (deviance)

11. ods select globaltests parameterestimates; proc logistic data=s5238.chdage ; model chd(event="1")=age; run;