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Maybe someone can help me or at least give me some clues.

I have 1057 patients all with different types of prostheses. One of them seems to have a higher revision rate than the others.

total numbers:
prosthesisA 662
prosthesisB 162
prosthesisC 151
other       82

revision rate:
prosthesisA 9   1,36%
prosthesisB 11  6,79%
prosthesisC 3   1,99%
other       4   4,88%

Could anyone tell me how I can show whether the revision rate of prothesisB (6,79%) is significantly higher or not compared to the other prostheses (incl. "other")?

Thank you & kind regards

Edit: Is it possible to compare only the prosthesisB with all others at once? I've created the following contingency table:

        prostB  other   total
Rev     11      16      27
noRev   162     868     1030
        173     884     1057

Odds-Ratio = (11*868)/(16*162) = 3.68
p-Value (Fisher Test) = 0.001

Can I say now that the chances for a revision with prosthesisB are ~3.5 times higher compared to all others? Is this plausible since the p-Value of the Fisher's exact test is highly significant?

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  • $\begingroup$ When you say "compared to the others", do you mean "compared to prosthesisA, prosthesisC and other", or "compared to other"? $\endgroup$ – Henry Sep 17 '11 at 23:03
  • $\begingroup$ Yeah, sorry. I should have stated it clearer. I mean compared to all other prosthesis including "other". $\endgroup$ – TheLostOne Sep 17 '11 at 23:19
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You should be careful about formulating your hypotheses after seeing the data. Instead of this, what I would do is a logistic regression with the IV being body part.

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  • $\begingroup$ I can probably only perform the logistic regression if I have the raw data, correct? $\endgroup$ – TheLostOne Sep 20 '11 at 17:34
  • $\begingroup$ I've added an own approach to the original answer. Do you think it's correct? Thank you! $\endgroup$ – TheLostOne Sep 20 '11 at 19:03
  • $\begingroup$ Yes, you need the raw data to do the logistic. Your approach does what I said to be careful about. You can DO it, but it's a bit of fishing, and the resultant p-values are not correct. $\endgroup$ – Peter Flom Sep 23 '11 at 11:29
  • $\begingroup$ Thank you Peter! I think my solution should do it for now. $\endgroup$ – TheLostOne Sep 25 '11 at 22:00

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