Correct for variables in ANOVA

Question

Hi.

I'm really struggling with this and I'm sure I'm missing something really stupid.

I have a set of people who either have a clinical manifestation (X), and so I am doing a series of ANOVAs to present the data in a table that will essentially have something like the table below. There is a variable of interest that I expect is associated with X, so I would like to know if there are group differences.

VariableX presentX AbsentpAge0.01*Duration0.01*Variable of interest (continuous)0.01*

Obviously there are more columns. My problems is that Age and Duration differ between the groups, and then the mean for the variable of interest does too. I want to know if there's a way I can get the 'p value' for the comparison of the mean for the variable of interest for X present vs absent, to make sure the difference isn't just a function of age and duration.

Is it possible with the X by Y -> Oneway = ANOVA platform? Or should I do it in a nominal logistic regression?

paigemiller · Answer

Seems to me that if you heve include Age in the model, then you have indeed corrected for the affect of Age.

Without reading the paper that contains the example you provide, I can't comment on the example you give.

stat_sas · Answer

Hello,

May be the following code can generate the desired results.

ods output MODELANOVA=MODELANOVA;

proc anova data=have;

class X;

model Y=X;

run;

quit;

proc print data=MODELANOVA;

run;

neurojmp · Answer

Mmm...

I'll make up some variables:

Patients with migraine

Patients without

Male/Female

23/23

21/220.910

Age

70.24±9.6

66.47±8.00.048*Depression index

83.05±12.4

90.27±7.40.001*

Muscle pain index13.96±1.4

14.70±0.5

0.008*

That would be a strange study.

Anyway, given this example, we can see that all three variables differ across the two groups. The most interesting difference is the 'Muscle pain index'. However, I have reason to believe that the difference in 'Age' and 'Depression' might explain that, rather than a true difference in patients with migraine.

I can do a nominal logistic regression (Fit Model in JMP) with 'Migraine' as the outcome variable (Y in JMP), and 'Age', 'Depression Index' and 'Muscle pain index' as predicting variables (X in JMP). The result is that the muscle pain index has a OR that is significant even when the effect of the other two is taken into account. However, I have seen people report things like this:

I don't think those p values are from a regression, and they don't list anything else that would make me think they did a regression to get them. I was wondering if there is another way to correct for things like 'Age' and when doing ANOVAs like I did above.

Thanks