# Comparing odds ratio of sample to odds ratio of population?

How would one compare the odds ratio of a sample to that of the odds ratio of its source population? For instance:

I have child murder records/data from mortuaries for a geographical area (my "population"). Let's say I use a regression model (e.g. Poisson) with a regressor variable: race of child (black vs white), and I calculate that odds of child being black is 1.14 vs white.

Now I do the same exercise but for newspaper coverage in the same geographical area and time period, and end up with odds of black child murder being reported is 0.74.

If I theoretically subtract the crime coverage OR (0.74) from the epidemiological OR (1.14),I should get an estimate of media undereporting. But given that my two samples are dependant and non-parametric, how would I go about doing this?

• Hmmm, so should I follow Frank's or Peter's advice? @Frank would you explain a bit further as to how one would go about calculating the ratio of the odds ratio please? – The_Dude Oct 20 '14 at 22:00

1. When your 2 data sources are linked. This means for every child murder cases, you know whether it was reported or not. In this case, create a response variable $y_i$ and let $y_i =1$ if the $i$th murdered child was reported in the news and $y_i =0$ if unreported. You then use logistic regression with $y$ as response variable and race as your covariate. The odds ratio of race would be what you need.