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I have binomial data infected/not-infected on individuals of a sample from different years for two different infections. I have used prop.trend.test to test for trend for each infection.

I want to test if there is a trend in the ratio of infected/not-infected between the two infections. Since a ratio could vary between 0 and ∞, what test is appropriate?

For testing trends in proportins, some have suggested glm with family binomial. Can i use glm with a different family?

What test can I use to prove there is an upward trend in time series of ratios assesment in R? suggests using the Cochran-Armitage test (which I think is the same as prop.trend.test) or logistic regression. Not sure if it is suitable in the case of ratios, though.

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you may not need this answer anymore, but I'm doing a series of trend analyses I think are similar looking at rates of antibiotic resistance in different populations over time. I'm using prop.trend.test to proxy for Cochran-Armitage test (seems VERY similar if not exactly the same). This tests whether or not there is a significant trend, but doesn't speak to the shape.

To test the linearity and direction of the trend, you can use lm...since our rates vary over time I add a quadratic term (our trend is clearly non-linear). I'm using this format:

> fit<-lm(m$prop ~ m$score + I(m$score^2)) 

where prop are the proportions and score is a 1:n count by year. Allows you to test the linear and quadratic terms at once.

I'm following the methods used in a previous paper but working a bit blind; would like to hear if I'm wrong!

Best of luck.

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