Statistics Help @ Talk Stats Forum - Biostatistics

Multivariate regression

KPW — Thu, 23 May 2013 13:11:09 GMT

What is the most suitable way to assess the effect several independent ordinal variables have on a single nominal variable ?

For example the chance of a tumour being malignant predicted by the
1. The presence of microcalcification
2. Definition of the margins
3. Relative echogenicity etc

I'm aware that if they were scale variables a Multiple linear regression analysis would do. I'm wondering what would be the best way to analyse the relative influence of these ordinal on the dependent variable.

Any help is much appreciated.

Colinearity, Logistic GEE

jamesmartinn — Wed, 22 May 2013 21:48:58 GMT

Hi!

I'm running a model and I think I've ran up against a colinearity issue. We have approximately 300,000 students in our dataset. For these students, we have information on their mothers and approximately 6000 kids have missing mother information. We've decided to include 'missing' as a category for the mother covariates :

age of 1st pregnancy; less than 19, greater or equal to 19, and missing
immigration status: immigrant, non-immigrant, and missing.

If I include these variables, among the other kid level characteristics, in my logistic GEE model, the parameter estimates for the 2 mother level variables are odd.

For age at 1st preg, I'm able to get an OR estimate for Missing vs <19 and greater equal to 19 vs < 19.

For Immigration Status: I'm able to get an estimate for immigrant vs non-immigrant, and the estimate for Missing category vs non-immigrant comes out to 0, and there is no pvalue associated with it either.

I'm using SAS proc Genmod.

I'm thinking colinearity might be an issue as for the two variables, the individuals in each missing category are the same kids. If i run a univariate analysis for each variable, I'm able to estimate all pair-wise OR.

Any suggestions?

Which stat? Difference of two means. T-test paired vs unpaired

detsb2011 — Wed, 22 May 2013 14:22:06 GMT

Hi guys. I'm trying to determine if the difference between two groups of data are statistically significant.

Looking at mri, I am measure the volume of the left atrium using two different methods.
I am using the same set of images for each of the two methods. I think they are independent samples as one measurement does not directly influence the other measurement, but I wonder if I'm thinking about this wrong. Or maybe I'm using the wrong test?

Thanks guys.