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(to Martin) Hi, this is your namesake, Mrdice. I'm into the logical fallacies at the moment, and I noticed you moved some articles around. For example, you put the spotlight fallacy together with biased sample. Is it alright with you if I give each fallacy, however closely related it is to another, its own page? Most fallacies are in some way or another related to eachother, and if we're going to put similar ones together, it would be a huge job, even more so because some of them belong to different catagories at the same time. My idea is to give each one its own page, and then mention at the bottom of the page to which ones they're related. Mrdice 03:19, 2004 Feb 16 (UTC)
This isn't necessarily best; it can be quite the opposite. Those who care most aren't bound to be true reflections of the population, especially if there's more room or inclination for people to care (or not) one way than the other. I can imagine this: Some government proposal has already been given the green light or even just been implemented. Many people were in favour of it, but they are already set to get their way and so might not bother voting. OTOH those who are against the idea are likely to flood the poll in protest.
It's also possible that the statment of a poll can be biased, by stating only one side of the argument. I can imagine this leading to biased results.... -- Smjg 15:31, 17 Jun 2005 (UTC)
This article has turned into a childish description of one specific type of misuse of statistics. Biased sampling has many forms and is sometimes unavoidable, but when the type of bias in the sampling mechanism is known it can be taken into account and possibly corrected in the analysis (that is, one can draw inference for the unbiased population given a biased sample). So it needs a major rewrite I cannot provide at the time.-- Boffob 18:23, 12 January 2007 (UTC)
This could use an overhaul in spelling and grammar check. If it weren't so late I'd do it myself. I'll come around and do it sometime if no one else wants to. (forgot to sign my post!) Imasleepviking 13:46, 1 February 2007 (UTC)
There are some sentence fragments as well: "Provided that certain conditions are met (chiefly that the sample is drawn randomly from the entire sample) these samples."??? —Preceding unsigned comment added by Nimajji ( talk • contribs) 02:53, 25 March 2009 (UTC)
I don't have time to discuss it much now, but I want to mention that there are many methods that can take different forms of biased sampling into account (not just reweighting of badly balanced samples), and there are cases where ignoring the bias will still lead to consistent (if inefficient) estimates of the parameters of interest (or a subset of them). So saying that estimates will always be erroneous and that statistical methods always assume that samples are representative of the target population is simply untrue. Though I reverted some recent changes made by an anonymous IP, I agree that the "problems with biased samples" section needs some rewriting.-- Boffob ( talk) 01:35, 26 January 2008 (UTC)
The content of the Spotlight Fallacy section of this article has been identified as plagiarism - it seems to sourced verbatim from a copyrighted source without attribution. The allegation of plagiarism can be found here: http://www.fallacyfiles.org/archive022009.html#02152009 and the apparent original source here: http://www.nizkor.org/features/fallacies/spotlight.html. I suggest someone either write an original entry or get permission to use this material in Wikipedia (and add an attribution). Thanks, Outeast —Preceding unsigned comment added by 193.85.230.200 ( talk) 12:43, 19 February 2009 (UTC)
An interesting twist on this, as it appears that the plagiarizer was the original author. See this (likely to be archived hereabouts). -- Hoary ( talk) 15:56, 28 March 2009 (UTC)
The result of the move request was page moved. Vegaswikian ( talk) 22:06, 22 November 2009 (UTC)
Biased sample →
Sampling bias —
As seen in
Template:Biases, every bias-article that has the ability to do so is in the ___ bias format, except this one. I think the unusual naming originally was a way to make it appear different from selection bias, but I've tried to rather explain the difference in the article itself, so any extraordinary name is no longer required.
Mikael Häggström (
talk)
16:31, 14 November 2009 (UTC)
partial negative. A problem is that "Sampling bias" is ambiguous, as it could be interpreted as "sampling the bias". Why say "biased sample" is unusual ... if you have a biased sample you have a biased sample, it would be more unusual to say you have a sample with sampling bias, as that is longer. However, the article uses both terms in what looks to be appropriate ways in different places, so one or other term would not be excluded whatever is done. Melcombe ( talk) 13:19, 18 November 2009 (UTC)
Pro I arrived at this page via the redirect. "Sampling the bias" is a novel expression to me, and I don't know what you mean by it. Could you provide examples? Paradoctor ( talk) 15:29, 19 November 2009 (UTC)
As described at the top of this article, ascertainment bias is apparently the same as sampling bias. Mikael Häggström ( talk) 17:26, 14 November 2009 (UTC)
The merge of sampling and ascertainment biases is extremely misleading. As mentioned above, ascertainment bias is an ex post error of judgement created by nonprobability sampling, whereas sampling bias occurs mostly ex ante during data collection. Merging both notions does not help to understand either. If you want to use an umbrella term, it should be selection bias.
I strongly recommend separating all notions, with illustrations:
An expert judgement would be needed to verify my claim, but I strongly believe that something is very wrong with the current state of the entry. -- -- phnk ( talk) 19:57, 21 January 2011 (UTC)
Although ascertainment bias might be a type of sampling bias, they are certainly not the same. It's extremely odd that the articles have been merged, such that ascertainment bias is not described at all. 188.29.224.235 ( talk) 11:25, 13 July 2012 (UTC)
I merged ascertainment bias to here, but most examples were already mentioned, and I found it unnecessary to have multiple examples for each type. Yet, if you find any of these very important, feel free to add them too. Mikael Häggström ( talk) 05:24, 4 May 2010 (UTC)
For example, to find the male/female ratio in a country it is not necessary to count everyone in the country: selection of a statistical sample of the population will be adequate. The way the sample is selected can influence the result. For example, if the residents of a housing project for elderly persons was counted, the result could be biased in favor of females, who statistically live longer than males. A simple classroom demonstration of ascertainment bias is to estimate the primary sex ratio (which we know to be around 1:1) by asking all female students to report the ratio in their own families, and comparing the result with the same question asked of male students. The females will collectively report a higher ratio of females, as all families having only male children are excluded by the selection criterion. The males will report a higher ratio of males, for the complementary reason. Ascertainment bias is important in studying the genetics of medical conditions, since data are typically collected by physicians in a clinical setting. The results may be skewed because the sample is of patients who have seen a physician, rather than a random sample of the population as a whole. Berkson's paradox illustrates this effect. Often, robust experimental design can minimize this effect. Another way to deal with this effect is to take the non-random sampling into account when analyzing results. |
The section on "Historical Examples seems to contain an error. It asserts that the Tribune came out with the "Dewey Defeats Truman" headline due to reliance on a "phone survey". Yet the source cited for this section says something quite different: http://www.uh.edu/engines/epi1199.htm This source asserts that the Gallup Poll take for the election was taken two weeks before the election, and not updated. Nothing is said about this having been a "phone poll," and the actual reason for the incorrect headline was the Tribune's reliance on old data, not a "phone poll". I think an earlyer portion of the article discussing the 1936 Landon-Roosevelt election has been conflated with the Dewey-Truman material. —Preceding unsigned comment added by 74.92.174.105 ( talk) 23:46, 19 May 2011 (UTC)
There is a short article on samlple selection and consistency of estimators, that discusses different sample selection equations, and would like to link to it. See it here. Let me know if it would be fine.
- I have now added the link for selection equations (15.Nov2011) — Preceding unsigned comment added by Esben.juel ( talk • contribs) 18:01, 15 November 2011 (UTC)
![]() | This article is rated C-class on Wikipedia's
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Daily pageviews of this article
A graph should have been displayed here but
graphs are temporarily disabled. Until they are enabled again, visit the interactive graph at
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(to Martin) Hi, this is your namesake, Mrdice. I'm into the logical fallacies at the moment, and I noticed you moved some articles around. For example, you put the spotlight fallacy together with biased sample. Is it alright with you if I give each fallacy, however closely related it is to another, its own page? Most fallacies are in some way or another related to eachother, and if we're going to put similar ones together, it would be a huge job, even more so because some of them belong to different catagories at the same time. My idea is to give each one its own page, and then mention at the bottom of the page to which ones they're related. Mrdice 03:19, 2004 Feb 16 (UTC)
This isn't necessarily best; it can be quite the opposite. Those who care most aren't bound to be true reflections of the population, especially if there's more room or inclination for people to care (or not) one way than the other. I can imagine this: Some government proposal has already been given the green light or even just been implemented. Many people were in favour of it, but they are already set to get their way and so might not bother voting. OTOH those who are against the idea are likely to flood the poll in protest.
It's also possible that the statment of a poll can be biased, by stating only one side of the argument. I can imagine this leading to biased results.... -- Smjg 15:31, 17 Jun 2005 (UTC)
This article has turned into a childish description of one specific type of misuse of statistics. Biased sampling has many forms and is sometimes unavoidable, but when the type of bias in the sampling mechanism is known it can be taken into account and possibly corrected in the analysis (that is, one can draw inference for the unbiased population given a biased sample). So it needs a major rewrite I cannot provide at the time.-- Boffob 18:23, 12 January 2007 (UTC)
This could use an overhaul in spelling and grammar check. If it weren't so late I'd do it myself. I'll come around and do it sometime if no one else wants to. (forgot to sign my post!) Imasleepviking 13:46, 1 February 2007 (UTC)
There are some sentence fragments as well: "Provided that certain conditions are met (chiefly that the sample is drawn randomly from the entire sample) these samples."??? —Preceding unsigned comment added by Nimajji ( talk • contribs) 02:53, 25 March 2009 (UTC)
I don't have time to discuss it much now, but I want to mention that there are many methods that can take different forms of biased sampling into account (not just reweighting of badly balanced samples), and there are cases where ignoring the bias will still lead to consistent (if inefficient) estimates of the parameters of interest (or a subset of them). So saying that estimates will always be erroneous and that statistical methods always assume that samples are representative of the target population is simply untrue. Though I reverted some recent changes made by an anonymous IP, I agree that the "problems with biased samples" section needs some rewriting.-- Boffob ( talk) 01:35, 26 January 2008 (UTC)
The content of the Spotlight Fallacy section of this article has been identified as plagiarism - it seems to sourced verbatim from a copyrighted source without attribution. The allegation of plagiarism can be found here: http://www.fallacyfiles.org/archive022009.html#02152009 and the apparent original source here: http://www.nizkor.org/features/fallacies/spotlight.html. I suggest someone either write an original entry or get permission to use this material in Wikipedia (and add an attribution). Thanks, Outeast —Preceding unsigned comment added by 193.85.230.200 ( talk) 12:43, 19 February 2009 (UTC)
An interesting twist on this, as it appears that the plagiarizer was the original author. See this (likely to be archived hereabouts). -- Hoary ( talk) 15:56, 28 March 2009 (UTC)
The result of the move request was page moved. Vegaswikian ( talk) 22:06, 22 November 2009 (UTC)
Biased sample →
Sampling bias —
As seen in
Template:Biases, every bias-article that has the ability to do so is in the ___ bias format, except this one. I think the unusual naming originally was a way to make it appear different from selection bias, but I've tried to rather explain the difference in the article itself, so any extraordinary name is no longer required.
Mikael Häggström (
talk)
16:31, 14 November 2009 (UTC)
partial negative. A problem is that "Sampling bias" is ambiguous, as it could be interpreted as "sampling the bias". Why say "biased sample" is unusual ... if you have a biased sample you have a biased sample, it would be more unusual to say you have a sample with sampling bias, as that is longer. However, the article uses both terms in what looks to be appropriate ways in different places, so one or other term would not be excluded whatever is done. Melcombe ( talk) 13:19, 18 November 2009 (UTC)
Pro I arrived at this page via the redirect. "Sampling the bias" is a novel expression to me, and I don't know what you mean by it. Could you provide examples? Paradoctor ( talk) 15:29, 19 November 2009 (UTC)
As described at the top of this article, ascertainment bias is apparently the same as sampling bias. Mikael Häggström ( talk) 17:26, 14 November 2009 (UTC)
The merge of sampling and ascertainment biases is extremely misleading. As mentioned above, ascertainment bias is an ex post error of judgement created by nonprobability sampling, whereas sampling bias occurs mostly ex ante during data collection. Merging both notions does not help to understand either. If you want to use an umbrella term, it should be selection bias.
I strongly recommend separating all notions, with illustrations:
An expert judgement would be needed to verify my claim, but I strongly believe that something is very wrong with the current state of the entry. -- -- phnk ( talk) 19:57, 21 January 2011 (UTC)
Although ascertainment bias might be a type of sampling bias, they are certainly not the same. It's extremely odd that the articles have been merged, such that ascertainment bias is not described at all. 188.29.224.235 ( talk) 11:25, 13 July 2012 (UTC)
I merged ascertainment bias to here, but most examples were already mentioned, and I found it unnecessary to have multiple examples for each type. Yet, if you find any of these very important, feel free to add them too. Mikael Häggström ( talk) 05:24, 4 May 2010 (UTC)
For example, to find the male/female ratio in a country it is not necessary to count everyone in the country: selection of a statistical sample of the population will be adequate. The way the sample is selected can influence the result. For example, if the residents of a housing project for elderly persons was counted, the result could be biased in favor of females, who statistically live longer than males. A simple classroom demonstration of ascertainment bias is to estimate the primary sex ratio (which we know to be around 1:1) by asking all female students to report the ratio in their own families, and comparing the result with the same question asked of male students. The females will collectively report a higher ratio of females, as all families having only male children are excluded by the selection criterion. The males will report a higher ratio of males, for the complementary reason. Ascertainment bias is important in studying the genetics of medical conditions, since data are typically collected by physicians in a clinical setting. The results may be skewed because the sample is of patients who have seen a physician, rather than a random sample of the population as a whole. Berkson's paradox illustrates this effect. Often, robust experimental design can minimize this effect. Another way to deal with this effect is to take the non-random sampling into account when analyzing results. |
The section on "Historical Examples seems to contain an error. It asserts that the Tribune came out with the "Dewey Defeats Truman" headline due to reliance on a "phone survey". Yet the source cited for this section says something quite different: http://www.uh.edu/engines/epi1199.htm This source asserts that the Gallup Poll take for the election was taken two weeks before the election, and not updated. Nothing is said about this having been a "phone poll," and the actual reason for the incorrect headline was the Tribune's reliance on old data, not a "phone poll". I think an earlyer portion of the article discussing the 1936 Landon-Roosevelt election has been conflated with the Dewey-Truman material. —Preceding unsigned comment added by 74.92.174.105 ( talk) 23:46, 19 May 2011 (UTC)
There is a short article on samlple selection and consistency of estimators, that discusses different sample selection equations, and would like to link to it. See it here. Let me know if it would be fine.
- I have now added the link for selection equations (15.Nov2011) — Preceding unsigned comment added by Esben.juel ( talk • contribs) 18:01, 15 November 2011 (UTC)