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If nothing else, this paragraph requires citations. Holm-Bonferroni is one of many sequential Bonferroni-type approaches to controlling the familywise error rate in a set of tests. Among these many approaches, it is not even particularly powerful---Hochberg's approach is, for example, guaranteed to be no less powerful and is in many cases more powerful. The paragraph should be changed to reference two classes of more pwoerful tests: (1) sequential Bonferroni-type tests that control the familywise error rate, and (2) Benjamini-Hochberg type tests that control the false discovery rate. Specific reference to an individual test such as the Holm's is out of place, as it appears to provide preference to one of many alternatives. —Preceding unsigned comment added by 71.48.130.128 ( talk) 13:21, 27 October 2009 (UTC)
Though related, the Bonferroni and Šidák tests rely on different assumptions and lead to generally different results. It is confusing to discuss both on a page labeled "Bonferroni correction." —Preceding unsigned comment added by 71.48.130.128 ( talk) 13:24, 27 October 2009 (UTC)
It says "one way of maintaining the familywise error rate is to test each individual hypothesis at a statistical significance level of 1/n times what it would be if only one hypothesis were tested", i.e., alpha_corrected = alpha/n. The formula given is *another correction*, which is "applicable for two-sided hypotheses, multivariate normal statistics, and positive orthant dependent statistics, it is not, in general, correct (Shaffer 1995)". See http://mathworld.wolfram.com/BonferroniCorrection.html —Preceding unsigned comment added by Leonardo.hamilton ( talk • contribs) 10:58, 20 February 2009 (UTC)
I have added extra references to this article so that people can conveniently find out more about this method. I have also added a direct link to Thomas Perenger's critique of the Bonferroni method, as it is cited in the three other references I have added. Michael Glass 13:23, 9 June 2007 (UTC)
I'm not sure about the point of adding this article by Perenger. It is a seriously flawed article in that you most definitely are not just rejected the global null hypothesis, but in fact also the individual hyphothesis. All of Perenger's arguments along of the lines of "And type II errors are no less false than type I errors" are rather pointless, if one pretends to perform multiple tests at a fixed type I error rate. One a whole the author just does not understand the Bonferroni adjustments. A much more reasonable criticism would be that Bonferroni-Holm is uniformly more powerful, but for example it's much harder to obtain valid Confidence intervals for the Bonferroni-Holm procedure (there's a recent paper on how to do it by Bretz et al., but these confidence intervals are surprisingly not always contained within the Bonferroni ones). Baselbonsai 00:01, 16 August 2008 (CET).
The other two articles "criticizing" Bonferroni are somewhat dubious also (the Moran and Nakagawa articles). It's notable that neither of those articles is in a statistical journal. And the Nakagawa article uncritically cites the clueless Perneger article mentioned above. 172.91.107.147 ( talk) 04:12, 26 March 2024 (UTC)
There is a need to clarify how the outcome of the multiple tests is judged .... "at least one test says reject", or "all tests say reject". Melcombe ( talk) 17:06, 29 April 2008 (UTC)
There was some notation implying that you specify the tests to be of size alpha/n, when they should be of size 1-(1-alpha)^(1/n)... That is, one minus the chance of not rejecting each test. Why would these things be written as 1-(1-alpha/n)? Brusegadi ( talk) 08:20, 14 February 2009 (UTC)
alpha/m is the Bonferroni correction (where m is the number of tests). 1-(1-alpha)^(1/m) is the Šidak correction. Those are two different formulas for two different (albeit similar) procedures. 172.91.107.147 ( talk) 20:47, 25 March 2024 (UTC)
Bonferonni correction was not developed by Bonferroni - it was developed by Dunn, based on a proof of an inequality. However, the proof of the inequality was not done by Bonferroni either, he extended it. I'll edit this when I have the time. Bonferroni correction is based on Boole's inequality - this is discussed in the article Stigler's law of eponymy by Steven Stigler. —Preceding unsigned comment added by Jeremymiles ( talk • contribs) 05:04, 18 March 2010 (UTC)
The statement "Second, in certain situations where one wants to retain, not reject, the null hypothesis, then Bonferroni correction is non-conservative." could do with a citation Worik ( talk) 00:47, 29 March 2010 (UTC)
The only source for the "Lou Jost" test is Lou Jost's own website - his suggestion does not seem to have been subject to any peer-review. I have removed the reference and added tags; if someone cannot dig up a good source, I will remove that section. Angio ( talk) 18:43, 15 November 2010 (UTC)
From the current article:
This claim should be sourced. Vegard ( talk) 17:06, 25 September 2012 (UTC)
The article says Dunn have wrote two papers in 1959 and 1961, but no paper in 1959 is cited in References section. I suppose the 1959 paper is - Dunn, O. J. (1959) Confidence intervals for the means of dependent, normally distributed variables. Journal of the American Statistical Association, 54, 613-621. Am I correct? Francesco Nagoya ( talk) 03:47, 15 February 2013 (UTC
Can we add the sentence "In order to do a Bonferroni Correction, divide your significance threshold by the number of hypotheses being tested" somewhere, preferably in the introduction? I know the article says this, but anyone who isn't a mathematician is going to have to read closely in order to extract that piece of information. (Assuming it is correct).
Agreed 100%. The introduction needs a specific example at the outset; not just for the technique, but also justifying why alpha is linearly divided by the number of hypotheses (or not multiplied for that matter). The article seems written to impress those who know, not those who do not. ELeP PerthAU ( talk) 14:40, 25 November 2015 (UTC)ELeP 20151125
The derivation of the correction substitutes having a conservative p-value for committing a type I error. The outcome is the same, but the presentation and therefore strictly speaking the logic is erroneous. I was thinking about how to correct it, but perhaps it should be handled by somebody more familiar with the subject matter's conventional presentation. — RFST ( talk) 08:37, 12 August 2014 (UTC)
In this edit by an IP a WP:RS was removed as being "full of misinformation". I reverted the edit , because I want a full discussion of what the supposed misinformation is.-- Wuerzele ( talk) 17:28, 17 September 2016 (UTC)
I'm not going to respond to Wuerzele's ad hominem attacks, other than to note the irony of his complaints about edit warring and the creepiness of his attempts to figure out where I live. Let's try to avoid that kind of behavior, which is better suited for a YouTube comment section than an encyclopedia, and which I'm sure violates some Wikipedia policy or another. Instead, let's focus on the issue at hand, which is how to build a better article. With that in mind, we should ask, "what does the Perneger link add to the article?" It contains no unique correct information whatsoever, and plenty of wrong information. As one researcher observed, it "consists almost entirely of errors" ( http://www.bmj.com/content/318/7176/127.2). Therefore, recommending it as a reference DOESN'T HELP AND MIGHT HURT.
One editor has asked for a peer-reviewed source refuting Perneger, which is a reasonable request. A good example of a peer-reviewed article that points out Perneger's cluelessness on the topic is the Goeman & Solari paper (from Statistics in Medicine, a respected statistical journal) that is cited in this article. It points out two very fundamental "misunderstandings" at the heart of Perneger's arguments: number 1 that Bonferroni assumes independence, and number 2 that Bonferroni only protects in the case of the global null. It's not that Perneger's opinions on these things are controversial, it's that he's objectively, mathematically wrong and doesn't seem to understand how Bonferroni correction relates to probability at its most basic level. This has been pointed out in the Goeman & Solari paper, in the Bender & Lange response in BMJ, in Aickin's letter to the editor mentioned above, and elsewhere. So the only conceivable way Perneger's paper could be usefully referenced in this article would be as an example in a section on common misunderstandings about the Bonferroni correction. To recommend Perneger's paper as either an expert opinion on the subject or as a debatable but relevant and mathematically accurate perspective is misleading. — Preceding unsigned comment added by 23.242.207.48 ( talk) 01:04, 24 September 2016 (UTC)
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@ Groceryheist: The change of title is inappropriate and inconsistent with article naming criteria. The new title, and accompanying article text change, are less recognizable (the old name is far more common in literature), less natural (few people are searching for the alternate name), less concise (without resolving any ambiguity), and less consistent (the old name was near universal throughout Wikipedia). Many things in science have unusual or "incorrect" names; It is not the role of Wikipedia to assert non-neutral, less common names as if they were consensus to reflect what some users think things "should be called". Echocancellation ( talk) 16:51, 27 June 2020 (UTC)
The result of the move request was: page moved. Ed6767 talk! 18:47, 30 June 2020 (UTC)
Dunn–Bonferroni correction → Bonferroni correction – The recent move by user Groceryheist was done unilaterally, with no discussion, and citing no sources, to reflect what some people think this statistical procedure "should have been called", even though it is by far a less common name, both elsewhere on Wikipedia and in published educational material. A quick search of journal articles would reveal that the old name was in more common use, and the one people would likely be searching for this article by. Echocancellation ( talk) 17:27, 27 June 2020 (UTC)
I think something is off. The Wiki article is about the correction for p-values (Bonferroni formulated that one in 1936, according to wiki). Dunn procedure is about confidence intervals (1958-1961). Albeit related, they are different things. Perhaps add an article about the Dunn procedure and cross-link both? thisbugisonfire ( talk) 21:50, 27 June 2020 (UTC)
Unfortunately, I don't agree with this edit and moving this page. I believe the cause for these recent edits is this tweet, but unfortunately it's wrong. The Dunn-Sidak correction is not the same as the Bonferroni correction, and one of the sources cited for this correction is an APA dictionary link, but it's clear the APA dictionary link is incorrect, just look at the original papers. I think the original intentions to give due credit are noble but the actual claims are incorrect and based on incorrect sources. Lesslikely ( talk) 22:27, 27 June 2020 (UTC)
- Given the inaccuracies of the claims, and the sources used to make the claim, I strongly support moving back the page immediately if we want to reduce as much confusion as possible. Lesslikely ( talk) 14:29, 28 June 2020 (UTC)
Ok, today it's already 29.June.2020 and the article still has the wrong title, pending an admin undo the move done on 27.June.2020. I have just now, however, edited the text to reflect the changes in this discussion, returning the name of the method to Bonferroni, while keeping and (hopefully) improving the mentions to Dunn's contribution. @ Groceryheist:: since you are able to move pages, might I kindly ask if you could reverse this one back to Bonferroni, and then perhaps we can start a discussion on renaming Sidak to Dunn-Sidak, as that would give Dunn the deserved credit? Thanks! Winkler ( talk) 16:06, 29 June 2020 (UTC)
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If nothing else, this paragraph requires citations. Holm-Bonferroni is one of many sequential Bonferroni-type approaches to controlling the familywise error rate in a set of tests. Among these many approaches, it is not even particularly powerful---Hochberg's approach is, for example, guaranteed to be no less powerful and is in many cases more powerful. The paragraph should be changed to reference two classes of more pwoerful tests: (1) sequential Bonferroni-type tests that control the familywise error rate, and (2) Benjamini-Hochberg type tests that control the false discovery rate. Specific reference to an individual test such as the Holm's is out of place, as it appears to provide preference to one of many alternatives. —Preceding unsigned comment added by 71.48.130.128 ( talk) 13:21, 27 October 2009 (UTC)
Though related, the Bonferroni and Šidák tests rely on different assumptions and lead to generally different results. It is confusing to discuss both on a page labeled "Bonferroni correction." —Preceding unsigned comment added by 71.48.130.128 ( talk) 13:24, 27 October 2009 (UTC)
It says "one way of maintaining the familywise error rate is to test each individual hypothesis at a statistical significance level of 1/n times what it would be if only one hypothesis were tested", i.e., alpha_corrected = alpha/n. The formula given is *another correction*, which is "applicable for two-sided hypotheses, multivariate normal statistics, and positive orthant dependent statistics, it is not, in general, correct (Shaffer 1995)". See http://mathworld.wolfram.com/BonferroniCorrection.html —Preceding unsigned comment added by Leonardo.hamilton ( talk • contribs) 10:58, 20 February 2009 (UTC)
I have added extra references to this article so that people can conveniently find out more about this method. I have also added a direct link to Thomas Perenger's critique of the Bonferroni method, as it is cited in the three other references I have added. Michael Glass 13:23, 9 June 2007 (UTC)
I'm not sure about the point of adding this article by Perenger. It is a seriously flawed article in that you most definitely are not just rejected the global null hypothesis, but in fact also the individual hyphothesis. All of Perenger's arguments along of the lines of "And type II errors are no less false than type I errors" are rather pointless, if one pretends to perform multiple tests at a fixed type I error rate. One a whole the author just does not understand the Bonferroni adjustments. A much more reasonable criticism would be that Bonferroni-Holm is uniformly more powerful, but for example it's much harder to obtain valid Confidence intervals for the Bonferroni-Holm procedure (there's a recent paper on how to do it by Bretz et al., but these confidence intervals are surprisingly not always contained within the Bonferroni ones). Baselbonsai 00:01, 16 August 2008 (CET).
The other two articles "criticizing" Bonferroni are somewhat dubious also (the Moran and Nakagawa articles). It's notable that neither of those articles is in a statistical journal. And the Nakagawa article uncritically cites the clueless Perneger article mentioned above. 172.91.107.147 ( talk) 04:12, 26 March 2024 (UTC)
There is a need to clarify how the outcome of the multiple tests is judged .... "at least one test says reject", or "all tests say reject". Melcombe ( talk) 17:06, 29 April 2008 (UTC)
There was some notation implying that you specify the tests to be of size alpha/n, when they should be of size 1-(1-alpha)^(1/n)... That is, one minus the chance of not rejecting each test. Why would these things be written as 1-(1-alpha/n)? Brusegadi ( talk) 08:20, 14 February 2009 (UTC)
alpha/m is the Bonferroni correction (where m is the number of tests). 1-(1-alpha)^(1/m) is the Šidak correction. Those are two different formulas for two different (albeit similar) procedures. 172.91.107.147 ( talk) 20:47, 25 March 2024 (UTC)
Bonferonni correction was not developed by Bonferroni - it was developed by Dunn, based on a proof of an inequality. However, the proof of the inequality was not done by Bonferroni either, he extended it. I'll edit this when I have the time. Bonferroni correction is based on Boole's inequality - this is discussed in the article Stigler's law of eponymy by Steven Stigler. —Preceding unsigned comment added by Jeremymiles ( talk • contribs) 05:04, 18 March 2010 (UTC)
The statement "Second, in certain situations where one wants to retain, not reject, the null hypothesis, then Bonferroni correction is non-conservative." could do with a citation Worik ( talk) 00:47, 29 March 2010 (UTC)
The only source for the "Lou Jost" test is Lou Jost's own website - his suggestion does not seem to have been subject to any peer-review. I have removed the reference and added tags; if someone cannot dig up a good source, I will remove that section. Angio ( talk) 18:43, 15 November 2010 (UTC)
From the current article:
This claim should be sourced. Vegard ( talk) 17:06, 25 September 2012 (UTC)
The article says Dunn have wrote two papers in 1959 and 1961, but no paper in 1959 is cited in References section. I suppose the 1959 paper is - Dunn, O. J. (1959) Confidence intervals for the means of dependent, normally distributed variables. Journal of the American Statistical Association, 54, 613-621. Am I correct? Francesco Nagoya ( talk) 03:47, 15 February 2013 (UTC
Can we add the sentence "In order to do a Bonferroni Correction, divide your significance threshold by the number of hypotheses being tested" somewhere, preferably in the introduction? I know the article says this, but anyone who isn't a mathematician is going to have to read closely in order to extract that piece of information. (Assuming it is correct).
Agreed 100%. The introduction needs a specific example at the outset; not just for the technique, but also justifying why alpha is linearly divided by the number of hypotheses (or not multiplied for that matter). The article seems written to impress those who know, not those who do not. ELeP PerthAU ( talk) 14:40, 25 November 2015 (UTC)ELeP 20151125
The derivation of the correction substitutes having a conservative p-value for committing a type I error. The outcome is the same, but the presentation and therefore strictly speaking the logic is erroneous. I was thinking about how to correct it, but perhaps it should be handled by somebody more familiar with the subject matter's conventional presentation. — RFST ( talk) 08:37, 12 August 2014 (UTC)
In this edit by an IP a WP:RS was removed as being "full of misinformation". I reverted the edit , because I want a full discussion of what the supposed misinformation is.-- Wuerzele ( talk) 17:28, 17 September 2016 (UTC)
I'm not going to respond to Wuerzele's ad hominem attacks, other than to note the irony of his complaints about edit warring and the creepiness of his attempts to figure out where I live. Let's try to avoid that kind of behavior, which is better suited for a YouTube comment section than an encyclopedia, and which I'm sure violates some Wikipedia policy or another. Instead, let's focus on the issue at hand, which is how to build a better article. With that in mind, we should ask, "what does the Perneger link add to the article?" It contains no unique correct information whatsoever, and plenty of wrong information. As one researcher observed, it "consists almost entirely of errors" ( http://www.bmj.com/content/318/7176/127.2). Therefore, recommending it as a reference DOESN'T HELP AND MIGHT HURT.
One editor has asked for a peer-reviewed source refuting Perneger, which is a reasonable request. A good example of a peer-reviewed article that points out Perneger's cluelessness on the topic is the Goeman & Solari paper (from Statistics in Medicine, a respected statistical journal) that is cited in this article. It points out two very fundamental "misunderstandings" at the heart of Perneger's arguments: number 1 that Bonferroni assumes independence, and number 2 that Bonferroni only protects in the case of the global null. It's not that Perneger's opinions on these things are controversial, it's that he's objectively, mathematically wrong and doesn't seem to understand how Bonferroni correction relates to probability at its most basic level. This has been pointed out in the Goeman & Solari paper, in the Bender & Lange response in BMJ, in Aickin's letter to the editor mentioned above, and elsewhere. So the only conceivable way Perneger's paper could be usefully referenced in this article would be as an example in a section on common misunderstandings about the Bonferroni correction. To recommend Perneger's paper as either an expert opinion on the subject or as a debatable but relevant and mathematically accurate perspective is misleading. — Preceding unsigned comment added by 23.242.207.48 ( talk) 01:04, 24 September 2016 (UTC)
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@ Groceryheist: The change of title is inappropriate and inconsistent with article naming criteria. The new title, and accompanying article text change, are less recognizable (the old name is far more common in literature), less natural (few people are searching for the alternate name), less concise (without resolving any ambiguity), and less consistent (the old name was near universal throughout Wikipedia). Many things in science have unusual or "incorrect" names; It is not the role of Wikipedia to assert non-neutral, less common names as if they were consensus to reflect what some users think things "should be called". Echocancellation ( talk) 16:51, 27 June 2020 (UTC)
The result of the move request was: page moved. Ed6767 talk! 18:47, 30 June 2020 (UTC)
Dunn–Bonferroni correction → Bonferroni correction – The recent move by user Groceryheist was done unilaterally, with no discussion, and citing no sources, to reflect what some people think this statistical procedure "should have been called", even though it is by far a less common name, both elsewhere on Wikipedia and in published educational material. A quick search of journal articles would reveal that the old name was in more common use, and the one people would likely be searching for this article by. Echocancellation ( talk) 17:27, 27 June 2020 (UTC)
I think something is off. The Wiki article is about the correction for p-values (Bonferroni formulated that one in 1936, according to wiki). Dunn procedure is about confidence intervals (1958-1961). Albeit related, they are different things. Perhaps add an article about the Dunn procedure and cross-link both? thisbugisonfire ( talk) 21:50, 27 June 2020 (UTC)
Unfortunately, I don't agree with this edit and moving this page. I believe the cause for these recent edits is this tweet, but unfortunately it's wrong. The Dunn-Sidak correction is not the same as the Bonferroni correction, and one of the sources cited for this correction is an APA dictionary link, but it's clear the APA dictionary link is incorrect, just look at the original papers. I think the original intentions to give due credit are noble but the actual claims are incorrect and based on incorrect sources. Lesslikely ( talk) 22:27, 27 June 2020 (UTC)
- Given the inaccuracies of the claims, and the sources used to make the claim, I strongly support moving back the page immediately if we want to reduce as much confusion as possible. Lesslikely ( talk) 14:29, 28 June 2020 (UTC)
Ok, today it's already 29.June.2020 and the article still has the wrong title, pending an admin undo the move done on 27.June.2020. I have just now, however, edited the text to reflect the changes in this discussion, returning the name of the method to Bonferroni, while keeping and (hopefully) improving the mentions to Dunn's contribution. @ Groceryheist:: since you are able to move pages, might I kindly ask if you could reverse this one back to Bonferroni, and then perhaps we can start a discussion on renaming Sidak to Dunn-Sidak, as that would give Dunn the deserved credit? Thanks! Winkler ( talk) 16:06, 29 June 2020 (UTC)