```Date: Mon, 9 Jan 2006 15:31:14 -0800 Reply-To: machelle Sender: "SAS(r) Discussion" From: machelle Organization: http://groups.google.com Subject: Re: New to Correlation Comments: To: sas-l@uga.edu In-Reply-To: <1136516590.137596.231210@g49g2000cwa.googlegroups.com> Content-Type: text/plain; charset="iso-8859-1" Hi there This is more of a stats question than a SAS question, and as others have indicated to you, you can't correlate the type of variables you are trying to correlate. To find the association between an ordinal (age group) and a nominal (mapped value)variable the correct test would be the Krusal-Wallis test. This test is also used when looking at a nominal variable with an interval or ratio variable if it's markedly non-normal. In a nutshell, the decision you make regarding which type of bi-variate analyses you perform is a function of the type of variables you have: 1) It they are both Interval/ratio variables, you can use proc corr and check the pearson correlation coefficient; 2) If they are both ordinal, or if they are both or one is interval/ratio but markedly non-normal, you'd move to the Spearman correlation coefficient; 3) If they are both nominal (i.e. they are categorical without any ordering involved, like colour or ethnicity) then you'd use a Chi-square test of independence; 4) if one is dichotomous (falls into one of 2 values like 'yes' 'no') and one is interval/ratio then you'd use a t-test; 5) if one is nominal with more than 2 categories, and the other was interval/ratio, you'd use ANOVA and finally, 6) For an Ordinal variable with a Nominal variable, you'd use Kruskal-Wallis. As I mentioned above, this test is also used when looking at a nominal variable with an interval or ratio variable if the latter is markedly non-normal. IF you wanted to start looking at associations and do modeling, then you'd be looking at doing an ordinal logistic regression where: your ordinal variable (age group) is your dependent variable mapped_value would be an independent variable and you could add other variables here to your model to check for confounding, interaction, and make an attempt to get a precise estimate of your effect. I know this probably all sounds a bit daunting, but you asked to be pointed in the right direction, and as someone else hinted, perhapse you might find it helpful to get some statistical analyst support? Grad students are usually good at things like this, and will usually be happy to earn some extra money to help them during their studies. I hope this helped... Machelle ```

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