Date: Fri, 24 Oct 2014 18:20:03 -0700
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[hidden email]Subject: Re: chi square but very disparate sample sizes
Rather than looking at a p-value, which will be small when the samples are large, you could look at the confidence interval on the risk difference (or risk ratio). Here is a good calculator for the CI on the risk difference (it uses a method recommended by Robert Newcombe, author of many articles on CIs for proportions and related measures, and more recently of a book).
http://vassarstats.net/prop2_ind.htmlRisk Difference = 0.007 <-- Is this big enough to be clinically significant?
95% confidence interval: no continuity correction
Lower limit = 0.0009 Upper limit = 0.0123
95% confidence interval: including continuity correction
Lower limit = 0.0007 Upper limit = 0.0124
Finally, the questions about independence of observations raised by Richard & Mike apply here too.
HTH.
sgthomson99 wrote
Hi everyone,
I need advice. I'm working with a big dataset.
If Population A is 4000 patients and there are 3.2% with the flu, and Population B is 53500 patients and 3.9% have the flu, is the difference in prevalence of the flu significant or not?
The clinic managers are saying use chi square 2x2 table, and then the prevalences are hugely significantly different. Just in my opinion because of the big sample size difference.
I'm being conservative and saying with such hugely different sample sizes, it's better to use 3.2/100 versus 3.9/100 so like a z test for proportions for the comparison -- and it's not significant.
Any suggestions greatly appreciated.
Susan
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