Hi Ian. Try GENLIN with a log-link binomial error distribution. Here's an

example from one of my files:

GENLIN default2 (REFERENCE=LAST) BY ed2 (ORDER=ASCENDING)

/MODEL ed2 INTERCEPT=YES

DISTRIBUTION=BINOMIAL LINK=LOG

/CRITERIA METHOD=FISHER(1) SCALE=1 COVB=MODEL

MAXITERATIONS=100 MAXSTEPHALVING=5

PCONVERGE=1E-006(ABSOLUTE) SINGULAR=1E-012

ANALYSISTYPE=3(WALD) CILEVEL=95 CITYPE=WALD

LIKELIHOOD=FULL

/MISSING CLASSMISSING=EXCLUDE

/PRINT CPS DESCRIPTIVES MODELINFO FIT SUMMARY SOLUTION (EXPONENTIATED).

Although it is a Stata resource, this UCLA page suggests another approach:

Poisson regression with a robust covariance matrix.

https://stats.idre.ucla.edu/stata/faq/how-can-i-estimate-relative-risk-using-glm-for-common-outcomes-in-cohort-studies/
HTH.

Ian Martin-3 wrote

> Hi All,

>

> It’s my understanding that reporting Odds Ratio (OR) for a common binomial

> outcome is less desirable — and misleading. Rather, I should be

> reporting Relative Risk (RR) for a disease outcome with a frequency of

> about 20% in a population.

>

> I can’t use CROSSTABS to get RR because my independent variables are

> continuous, and can’t see how to get REGRESSION>Binary Logistic to produce

> RR instead of OR.

>

> Any suggestions or workarounds?

>

> TIA,

> Ian

>

>

> Ian D. Martin, Ph.D.

>

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