Re: Binary logistic regression - poor models

Posted by David Marso on Apr 25, 2016; 11:07pm
URL: http://spssx-discussion.165.s1.nabble.com/Binary-logistic-regression-poor-models-tp5732023p5732026.html

I don't think it wise to toss everything into one big stew!
People probably form clusters WRT disease constellations and not all drugs are applicable for all diseases.
Peel back the onion Grasshopper.  Throw a little bit of theory into your GIGO?

dfva wrote

Hi all!

I am fairly novice in SPSS binary regression. I would like to carry out an analysis on the following topic:
- I want to predict a medical event (this is the heart failure)
I have the following predictors: age, gender, the existence of 12 different diseases for each patient (e.g diabetes mellitus) and cumulative doses for 42 drugs - so each patient can I describe with 58 variables. The existence variables have 'yes' and 'no' values, the cumulative drugs are variables with continuous values.

I know that age has effect on the dependent variable, and probably some other variables has also affect on the dependent variable, but it is unknown.

I would like to determine the effect of each variable.

I tried to put all variables in the covariates box, but it gave me very poor model.
Then I tried it in 3 step: in the first step age and gender, and in the second step the diseases, and in the third step the drugs. It resulted in very poor model as well.
Then I though I will test only one drog, and I put in the first step age and gender, and in the second step only one drug. The model was again very poor.
In all cases Rˇ2 values are under 0,1.  

In my sample the occurrence is only 10,1 percent.
If I make ROC analysis it shows very bad curve - fast straight across.

Could somebody help me, how can I solve this problem? Is binary logistic regression a good method for this problem? Even if the model is very poor??? Can I evaluate the p values for poor models or not???

Thank you!
Agnes