1. Categorical Data Analysis: When life fits in little boxes AnnMaria DeMars, PhD.

2. What are we going to do today? Basic statistics Logistic regression

3. An actual example Are you going to die soon?

4. Our data Kaiser Permanente Study of the Oldest Old, 1971-1979 and 1980-1988: [California] DEPENDENT VARIABLE: Dthflag = 1 if Died during study period 0 if alive at end of study period

5. Our data PREDICTOR VARIABLES: Gender nursehome = 0 if lived at home continuously 1 = admitted to nursing home at any time

6. STACKED BAR Figure 1

7. STACKED BAR Figure 2

8. Compare the effects

9. …How to get one: STACKED BAR CHART TASKS > GRAPHS

10. Stacked Bar Chart with SAS Enterprise

13. The Syntax PROC GCHART DATA=mydata.oldpeople; VBAR gender / SUBGROUP=dthflag TYPE= PCT INSIDE=PCT ;

14. Now a Brief Look at Logistic Regression

15. Our data PREDICTOR VARIABLES: Nursehome = lived in nursing home during study Age_comp = age when study began ERvisits= number visits to ER during study Gender

16. Odds ratio Value of 1.0 means : The odds are the same for the two groups, e.g., women are just as likely to die as men

19. Receiver Operator Charactistics SENSITIVITY - the percentage of true positives, the people we predicted would die who did SPECIFICITY - or true negatives, the number of people we said would NOT die, who did not

20. PERFECTION!

21. TASKS > REGRESSION > LOGISTIC

22. The Process: