# Application of Logistic Regression

I have the following data set:

Row    Patient        Freq of Sickness     Sick # of times(2 yrs)    Symp 1   Symp 2  Sym 3
1        A               60 days                        4              1        0       1
2        B               90 days                        10             0        1       1
3        C               40 days                        5              0        0       6
4        D               30 days                        0              1        0       0
5        E               80 days                        1              3        0       1

• What kind of logistic regression should I use if I need to predict the probability for each patient to be sick in the next year ? Also, need to calculate the maximum likelihood and odds ratio of each symp which contributes to the sickness.

• Should I consider Sick # of times(2 yrs) as ordinal or nominal ? I think Ordinal.

Presently, I am using PROC Logistic and PROC GENMOD in SAS to solve this problem. In GENMOD i used Cumulative logit and in PROC Logistic I have tried using both Ordered logit and un ordered Glogit. I got the best results when I used cumulative logit.

Any reference to study material would be highly appreciated.

Also is Logistic Regression the correct approach?

• Similar study available here – Metrics Jul 5 '13 at 16:19
• I don't see an outcome variable?? – ReliableResearch Jul 5 '13 at 21:11
• The outcome variable can be " Sick # of times". That's another confusion I have, that whether to use this as an independent variable or response variable. Because Sick # of time in past 2 years can also be a very good indicator. – learnlearn10 Jul 8 '13 at 12:51
• If number of times sick is the outcome, is logistic regression really the correct approach? – ReliableResearch Jul 11 '13 at 15:03
• I think we can use logistic regression to check the probability if the patient will be sick again or not. I used Sick # of times as the dependent variable in PROC LOGISTIC and got good results. Another thing that I am trying to do is to take each case as a separate row. When we do that, we will have 4 rows for patient A and 10 for B respectively. Let's see how that works out. – learnlearn10 Jul 11 '13 at 21:37