Timeline for Can I use Wilcoxon Signed-Rank paired Test to compare binary data?
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
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| Mar 30, 2019 at 15:18 | comment | added | Vasilis Vasileiou | Fixed that. Name of the corrected table is "tab" for future readers | |
| Mar 30, 2019 at 15:15 | history | edited | Vasilis Vasileiou | CC BY-SA 4.0 |
Fixed table for McNemar's test
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| Mar 27, 2019 at 11:48 | comment | added | Vasilis Vasileiou | You are welcome. Sounds solid! | |
| Mar 27, 2019 at 11:40 | comment | added | sda | Thank you very much for your comments. My data is paired and nominal (i.e., “1” or “0” for each case with two settings). The n~900. I have used the McNemar's Chi-squared test which returned a p-value <<5%. I conclude, that the change observed in my case was significant. | |
| Mar 27, 2019 at 8:53 | comment | added | Vasilis Vasileiou | The sample size. In the case of independent samples and when we want to assess the frequency difference H0:p1=p2 vs H2:Otherwise, the statistic that we derive is Z = ((p1hat - p2hat) - (p1 - p2))/(SE(p1_hat-p2_hat)) which under the null hypothesis of p1=p1=p becomes Z = (p1hat - p2hat) /(sqrt(p(1-p)(1/n1 + 1/n2))). The derived test statistic converges in distribution to N(0,1). This is what I meant by assumptions of CLT, that we basically need sufficiently large samples for this convergence to be valid. en.wikipedia.org/wiki/Pearson%27s_chi-squared_test#Assumptions | |
| Mar 27, 2019 at 2:24 | comment | added | Glen_b | No. I meant simply that I can see nothing in the central limit theorem itself that says anything about how to choose when the chi-squared approximation is not suitable. Your first sentence mentions "central limit theorem assumptions". Which assumption violations would make the chi-squared unsuitable but leave the Fisher exact test unaffected? | |
| Mar 27, 2019 at 1:03 | history | edited | Vasilis Vasileiou | CC BY-SA 4.0 |
I've added the case where Series 1 and Series 2 are observations of dependent random variables
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| Mar 27, 2019 at 0:51 | comment | added | Vasilis Vasileiou | @Glen_b Oh you mean that the outcomes of series 1 and 2 might not be independent? You are right, I will edit my answer to account for that case as well. Thanks for your correction, it was my bad to assume independence. | |
| Mar 26, 2019 at 23:53 | comment | added | Glen_b | Take a look at what the Central limit theorem actually says. Could you explain which of the assumptions of the central limit theorem (or indeed any of the central limit theorems, since there are several) are relevant to choosing whether to do a chi-squared test or something else? | |
| Mar 26, 2019 at 21:13 | history | answered | Vasilis Vasileiou | CC BY-SA 4.0 |