「華人戴明學院」是戴明哲學的學習共同體 ,致力於淵博型智識系統的研究、推廣和運用。 The purpose of this blog is to advance the ideas and ideals of W. Edwards Deming.

2009年1月30日 星期五

Does Bran Make the Man? What Statistics Really Tell Us

統計學爭議

技術 Wikipedia article "Bonferroni correction".

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2009年 01月 29日 13:26

你的性別取決於你媽懷你時吃什麼? 此題翻譯誤會正文

婦早餐時是否吃谷類食品會決定胎兒的性別?

英國一家科學期刊就這個問題展開了一場爭論,從中我們可以看出某些觀察性研究的結果不可輕信。

去 年四月,《英國皇家學會會報-B輯》(Proceedings of the Royal Society B)刊登了一篇研究報告──《你是由你母親吃什麼決定的》(You Are What Your Mother Eats),在全球引起巨大反響。來自艾克斯特大學和牛津大學的研究人員請740名懷孕婦女記錄下她們在孕期和懷孕之前的飲食。結果並不出人意料,孕婦懷 孕期的飲食和胎兒性別沒什麼聯系。

Michael Sloan

不過,懷孕期攝入熱量最多的孕婦中,有56%生了男孩;攝入熱量最少的孕婦中,有45%生了男孩。在研究涉及的132種單獨食物中,谷類早餐食品與生男孩的關系最為明顯。

怎麼會這樣?研究報告的作者表示,動物研究也發現在食物充足時更容易生育雄性後代:他們猜測孕婦的血糖含量較高可能有利於雄性胎兒存活,因為雄性胎兒比雌性略重。

美國的一些統計學家認為這是一派胡言,他們懷疑這個結論只是一大堆統計數據中偶然出現的錯誤關聯。

美 國國家統計科學研究院(National Institute of Statistical Sciences)的副主任斯坦﹒榮格(Stan Young)說,可以這麼看:拿到的一把牌中全是方片牌的可能性微乎其微,但要把范圍擴大到全世界的所有牌局,這還是有可能的。他獲得了上述研究數據,對 其重新進行了分析,並在本期《英國皇家學會會報》上撰文評論說,谷類食品攝入量與胎兒性別的關系純屬偶然。

研究報告的作者們則撰文反駁榮格的分析,以捍衛自己的研究發現。

除了有關谷類食品的爭論,統計學家和流行病學家還在這種觀察性研究中存在的偶然性問題上存在巨大分歧;所謂觀察性研究就是研究人員追蹤人們的生活習慣,尋找這些習慣與他們身體健康之間的關系,但在追蹤過程中完全沒有實施幹預。

統 計學家表示,此類研究經常會出現偶然性聯系,這也是為什麼研究結果許多都相互矛盾的原因。為了証明這一點,安大略的研究人員研究了住院患者的星座,發現射 手座的人容易骨折,雙魚座的人容易產生心臟問題,如此等等。這種聯系符合“具統計學意義”的傳統數學標準,但卻是完全偶然性的,換一個不同的樣本重新研 究,此前的結果就不存在了。

一些統計學家認為,研究人員在分析大量數據時應該採取更為嚴格的証明標準。一個方法是採取 Bonferroni調整,要求用相關數學公式除以變量的數目;如果研究的是100種食物,那麼必須有比尋常高100倍的關聯度才能被認為具統計學意義。 否則,統計學家表示只有進行嚴格的臨床試驗,對比一個控制組、一個測試組以及一個變量,才能真正証明因果關系。

流行病學家則認 為,Bonferroni調整忽視了許多合理發現,而且同時研究多少其他因素並不會影響研究結果。他們還指出,控制性的臨床試驗代價不菲、耗時持久,有時 還不道德。拿吸煙和肺癌之間關系的研究來說,許多觀察性研究都發現了這一點,但要迫使研究對象吸煙多年來証明這一點恐怕是不可能的。

在上述的谷類食品研究中,榮格認為,要使研究結果具統計學意義,孕婦懷孕中期的飲食數據應該被考慮進去。而經過這一調整,所謂谷類早餐食品與胎兒性別的關聯度就失去統計學意義了。他說,如果你先入為主地去挑選數據的話,你能找到可証實你任何預想的數據。

那篇研究報告的主要作者費奧娜﹒馬修斯(Fiona Mathews)反駁道,孕婦在懷孕中期的飲食根本無法影響成形胎兒的性別。馬修斯是艾克斯特大學的一名哺乳動物學講師。她表示,加入那些數據只是為了進行比較。

那麼谷類早餐食品會影響胎兒性別嗎?先別急。一個好經驗是耐心等待,看看再次進行這一觀察性研究時是否能得出同樣結果。馬修斯表示,她打算再次進行研究。

Does Bran Make the Man? What Statistics Really Tell Us


MELINDA BECK

Can eating breakfast cereal determine the sex of your baby?

A debate over that question in a British scientific journal shows why some observational studies should be taken with a big shaker of salt.

The original study, "You Are What Your Mother Eats," in the journal Proceedings of the Royal Society B, made headlines around the world last April. Researchers at Exeter and Oxford universities asked 740 pregnant women to record what they ate during pregnancy and just before. Not surprisingly, their diets during pregnancy had no correlation with their babies' gender.

[breakfast cereal] Michael Sloan

But 56% of women who consumed the most calories before conception gave birth to boys, compared with 45% of those who consumed the least. Of 132 individual foods tracked, breakfast cereal was the most significantly linked with baby boys.

How could that be? The authors said animal studies also found male offspring are more common in times of plenty; they speculated that higher glucose levels in mothers may favor the survival of male embryos, which are slightly heavier than females.

Baloney, said some U.S. statisticians, who suspected the finding was simply a false association that can occur by chance in a large set of data.

Making Sense of Studies

Following health news is a lot like watching a ping-pong match: reports linking fat or coffee or alcohol with various ills one week often get contradicted the next. Often, such findings come from observational studies that aren't as precise as randomized controlled trials. Some experts think they shouldn't be published until they've been confirmed with repeat studies.

What's your view? How much do you trust the health news you hear?

"Think of it this way: The probability of getting all spades in a given bridge hand is infinitesimally small, but in all the bridge games all over the world, somebody might," says Stan Young, assistant director of the National Institute of Statistical Sciences in Research Triangle Park, N.C. He obtained the study data, re-analyzed it and wrote a commentary in the journal's current issue saying the cereal finding was pure chance.

The study's authors wrote a rebuttal disputing Dr. Young's analysis and standing by their findings.

Behind the cereal squabble lies a deep divide between statisticians and epidemiologists about the nature of chance in observational studies in which researchers track peoples' habits and look for associations with their health but don't intervene at all.

(Read the Studies

Subscription to the journal or pay to access may be required)

Statisticians say random associations are rampant in such studies, which is why so many have contradictory findings. To prove the point, researchers in Ontario studied the astrological signs of hospital patients and found that Sagittarians are susceptible to fractures, Pisces are prone to heart failure, and so on. The links met the traditional mathematical standard for "statistical significance" but were completely random, and disappeared when the study was repeated with a different sample.

Some statisticians argue for a tougher standard of proof when researchers are fishing in large data sets. One method, a Bonferroni adjustment, requires dividing the usual mathematical formula by the number of variables; if 100 foods are studied, the link must be 100 times as strong as usual to be considered significant. Otherwise, statisticians say only strict clinical trials with a control group and a test group and one variable can truly prove a cause-and-effect association.

Epidemiologists argue that a Bonferroni adjustment throws out many legitimate findings, and that it's irrelevant how many other factors are studied simultaneously. They also note that controlled clinical trials are costly, time-consuming and sometimes unethical. The link between smoking and cancer, for example, was seen in many observational studies, but forcing subjects to smoke for years to prove it would be untenable.

In the cereal study, Dr. Young argues that the data collected on the mothers' diets at mid-pregnancy should be factored into the adjustment for statistical significance, and that when it is, the significance of breakfast cereal vanished. "If you can pick and choose your data after the fact, you can make them look however you want," he says.

"There's no way that the mother's diet in mid-pregnancy would affect the gender of her infant," counters Fiona Mathews, the lead author and a lecturer in mammalian biology at Exeter, who says that data was included only for comparison.

So does breakfast cereal affect a baby's gender? Don't paint the nursery yet. A good rule of thumb is to wait and see if an observation association pops up again when the study is repeated, something Dr. Mathews says she plans to do.





Printed in The Wall Street Journal, page D1

Copyright 2008 Dow Jones & Company, Inc. All Rights Reserved

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