11-02-2012 03:33 PM
I have something like shown below,'
Type of Case
CaseA CaseB CaseC
Diabetes N= N= N=
I did a contingency table of :
Diabetes with Cases
Aids with Cases
Headache with Cases
Fever with Cases
Found that the p-values are significant for a couple of them(less than 0.05)
What is the meaning of that statistically?
Also how to do a regression analysis....How do I proceed from there???
Any help is highly appreciated
11-02-2012 03:56 PM
Whenever a p value is less than 0.05, this indicates that the quantity being tested is statistically significant (at the alpha=0.05 level). In layman's terms, this particular arrangement of data that is tested was unlikely to have happened by random chance, it is probably a "real" effect.
You cannot do regression on this data. You need to have continuous X and continuous Y to do a regression.
11-02-2012 04:12 PM
Logistic regression is appropriate when you have a continuous X variable, and a categorical Y variable.
For example, if X is temperature, and Y is pass/fail status.
Among other things, logistic regression will compute the probability that you get a pass (or a fail) at a given temperature.
11-02-2012 04:22 PM
You've completed what's known as univariate analysis on your data, checking the category of one variable against others one at a time.
It sounds like you're looking to move on to the multivariate stage, looking at multiple variables together, and relationships between them.
The appropriate multivariate model depends on what your research question/hypothesis is and the structure of your data.
As you've shown all categorical data, my guess is a log-linear model, but that's a GUESS.
11-02-2012 05:39 PM
I'd say consult with a statistician (possibly a biostatistician) now .There really are too many things that would need to be considered and I've seen too many bad medical publications to help produce one.
Your local university probably has a consulting services that will be free of charge or low cost.
11-04-2012 09:21 PM
P value less than 0.05 is statistical significant if your possibility of committing the first mistake is .05 .
That means your H0 hypothesis (Type of Case and Headache are independent ) is not right.
.05 discover there are some correlation between Type of Case and Headache .
I recommend you also use corresponding analysis to check this relation more .