Re: Association between two nominal variables?

Posted by Dominic Lusinchi on Sep 19, 2006; 11:42pm
URL: http://spssx-discussion.165.s1.nabble.com/Association-between-two-nominal-variables-tp1071026p1071027.html

Kevin,

For a 2X2 table you can use the Phi statistic, available in the Crosstab
procedure under Statistics. Phi varies from 0 to 1: closer to 1, stronger
the association. Of course this assumes that the chi-square statistic is
significant.

You can also compute the crossproduct ratio, better known as the odds ratio:
[(1,1)X(2,2)]/[(1,2)X(2,1)]; where the first number is the row and the
second the column, and these represent the frequencies in each cell.

An odd ratio (OR) of 1 means there is no relationship between the two
variables. An OR>1 means greater likelihood of the outcome given the risk
factor; an OR<1 means you are less likely to have the outcome.

I say you have to compute this because SPSS does not: that is, not in the
crosstab procedure.

Cheers,

Dominic Lusinchi
Statistician
Far West Research
Statistical Consulting
San Francisco, California
415-664-3032
www.farwestresearch.com

-----Original Message-----
From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of
Secrist, Kevin
Sent: Tuesday, September 19, 2006 2:24 PM
To: [hidden email]
Subject: Association between two nominal variables?

Hello SPSS guru's,

I am a novice user trying to identify the association between two nominal
variables and two nominal outcomes.
the variables are labeled Peer Pal (yes/no) (1 or 0) and the outcome labeled
outpt (for outpatient service received) yes/no (1 or 0).
The N for Peer Pal 0 = 165 and the N for Peer Pal 1=674.

What test(s) can SPSS 12.0 perform to indicate the association between
variables and outcomes? and what would the expected value(s) be if the
association exists, is weak, or is strong?


Thanks

Kevin Secrist - Administrative Analyst, Associate
Butte County Behavioral Health
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Far better an approximate answer to the right question, which is often
vague, than the exact answer to the wrong question, which can always be made
precise.
Ann. Math. Stat. 33 (1962) - John w. Tukey