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[求助] 招募翻译:推断统计学、P值及评价假说的探索

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epiman 发表于 2018-6-6 10:26:15 | 显示全部楼层 |阅读模式
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诚征统计爱好者翻译此篇( O) \, M+ l- b3 B
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Inferential statistics, p-values, and the quest to evaluate our hypotheses
1 ]( E4 n5 X' K4 vhttps://peerj.com/blog/post/115284880344

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But I have increasingly come to believe that science was and is largely a story of success in spite of, and not because of, the use of this method. The method is called inferential statistics. Or more precisely, hypothesis testing. 但是我越来越相信科学无论在过去或是现在,很大程度上,是与这一方法的使用无关的成就。 The method I consider flawed and deleterious involves taking sample data, then appl ...
飐舟渚月 发表于 2018-6-6 10:26:16 | 显示全部楼层
But I have increasingly come to believe that science was and is largely a story of success in spite of, and not because of, the use of this method. The method is called inferential statistics. Or more precisely, hypothesis testing.
% f( J- s/ e) U! G但是我越来越相信科学无论在过去或是现在,很大程度上,是与这一方法的使用无关的成就。# m2 ], {1 m# x3 d# D
The method I consider flawed and deleterious involves taking sample data, then applying some mathematical procedure, and taking the result of that procedure as showing whether or not a hypothesis about a larger population is correct.( T. p. S' Y! `. {
我认为错误且有害的这一方法,包括收集样本数据、运行算术程序、并且用运算结果判断某个假设在人群中是否正确。" L  S" O; }% w9 s6 I: B4 `+ [4 r
Now, if you are familiar with the current debates about this method, you might think: “Somebody is yet again blaming p-values for everything.” But no, I am not. The p-value is a statistic that has the great advantage of being easily applied.: T2 e$ V# p  J' Y
现在,如果你熟悉目前有关这一方法的争论,你也许会想:“不过是又有人在四处指责p值。”然而非也,我并非如此。简单易操作的P值是很好的统计数值。
* D; ?  F% B$ B' v% Q" TUnfortunately, it seems that everybody I know, including myself, has used it in the wrong way.' ]/ y( n4 ^6 @# }' f1 H2 @
不幸的是,似乎我所认识的每一个人,包括我自己,一直在错误地使用它。
; p$ L7 w( {5 N( H' R5 Q1 ABut let me start by reporting a story about what a p-value is capable of doing. This story was told, at least in part and probably not for the first time, in a blog post by neuroscientist Ulrich Dirnagl.
& o0 }! X  O; v2 \# r! c# d) Y但是还是让我举一个例子来说明p值的用途吧。这个故事已经在神经学家Ulrich Dirnagl的博客文章中提到过,至少是说了一部分,而且你可能不是第一次听说它了。
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. c! {9 e2 h; f& \What went wrong?
8 u9 z& m, {7 H3 S是哪里出错了?
0 }- G; _& u9 RIn 2011, researchers at CERN worked on the so-called OPERA experiment and sent neutrinos through the Alps to be detected in central Italy. The neutrinos were found to be faster than light, even when the experiment was repeated. This was surprising, to say the least, and the p-value attached to the observation was smaller than the alpha level of p=0.0000003 that is required to announce a discovery in particle physics experiments involving collision data.% j# C9 R1 A! V" n9 o
在2001年,CERN的研究员在进行一个叫做OPERA的实验,还寄出中子到意大利中部进行检测,途经阿尔卑斯山。人们发现这类中子的运动速度水平超越光速,甚至反复实验依然能得到相同结果。这是十分惊人的,退一步说,该实验观察得到的p值——小于ɑ水平的p=0.0000003——都要求发表这一分子物理学实验碰撞数据中的发现。
5 M  H4 c* c( d; K, A( V1 P2 n9 BAlthough the researchers made clear that they were still searching for possible unknown systematic effects that might explain the finding, the news hit the media as: “Was Einstein wrong?”
2 N' o5 L% H5 L虽然研究员已表明,他们还在寻找可能的未知系统影响来解释这一现象,这一消息还是轰炸了媒体:“爱因斯坦错了吗?”
2 }8 h6 O3 \- _A few months later, the researchers announced the explanation for the surprising measurements: a cable had not been fully screwed in during data collection.2 N3 _4 C* p$ J9 P
几个月之后,研究员们公开对这一惊人的测量结果予以解释:收集数据时有一条电缆没有被拧紧。
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Statistical models usually include an implicit assumption that all cable connections are correct. (Image: State Farm via flickr.com)
& ]$ ?8 Y4 i+ r统计学方法的使用通常包含一些潜在假设前提,比如所有的缆线正确连接。(图源:State Farm via flickr.com)
7 i: P1 o4 \; [6 g" S2 H5 hDoes that mean p-values are unreliable? No, it means that we should not make inferential decisions based on p-values. Indeed, the p-value in the OPERA experiment was correct. As Sander Greenland explains, we should think of a p-value as referring not only to the null hypothesis but to the entire model it was computed from, including all assumptions such as that there were no measurement errors.
1 ~* w9 U; h+ Y, }2 `) j这是否意味着p值就是不可靠的呢?答案是否定的,这意味着我们不应该依靠p值进行推断决策。事实上,OPERA实验中的p值是正确的。正如Sander Greenland所言,当我们在考虑p值的时候,不应该仅仅想到H0,而是要想到求出它的整个模型,包括所有的假设,像是“没有测量误差”。0 X  ]* n8 M) t! |8 Q  p" r
A small p-value indicates that something is wrong with the model, but it does not indicate what is wrong.
6 J' l; a, [: ?- X3 Z一个小的p值意味着假设模型中存在错误,但是它并没有指出是哪里错了。6 g5 g5 G, H* i! y5 p
The original OPERA model included the null hypothesis “neutrinos are not faster than light.” However, it also included an assumption that the equipment was in perfect working order. As indicated by the extremely small p-value, the original model had a problem. But the researchers did a good job in finding an additional explanatory variable, and the new model — including the loose cable — successfully explained the observation that neutrinos appeared to travel faster than light.
* j/ ^2 T3 A4 |  `) X" e7 L原有的OPERA模型包含H0“中子不会快于光速。”然而,它也包含着“所有的仪器设备处在完美的工作状态”的假设。正如极小p值所指出的,原有的模型中存在问题。尽管如此,研究员们出色地寻找到其它的解释变量,并且建立新的模型——包含松了的缆线,成功地解释了中子快于光速的观察结果。
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第一次动手翻译科学文献,求楼主高手指点!谢谢!
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liweiyi19880202 发表于 2018-6-6 19:27:56 | 显示全部楼层
你好,如何联系你,我有意翻译
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 楼主| epiman 发表于 2018-6-7 16:46:55 触屏版 | 显示全部楼层
liweiyi19880202 发表于 2018-6-6 19:273 Z) ]# i' J+ o. Y9 e. I& w+ \
你好,如何联系你,我有意翻译

2 ?: L0 X; |3 v欢迎,跟帖翻译就是了。
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2291175099 发表于 2018-6-21 16:35:54 | 显示全部楼层
   你好,我先给您看前两段的翻译(括号中添加的是我自己的想法,与文章翻译无关),若您觉得可以,我再继续翻译;若您认为翻译不到位,请告知!谢谢!
3 c' ]/ g/ N8 D& a7 x     P值和显著性检验在科学研究中已经受到越来越多的审查(或者用推敲、研究?)。在表明假设是否成立时这些方法是如此精准?作者Valentin Amrhein看了许多我们无法用P值完全地解释的显著性检验的事例,以及新出现的目的是使得设计方案及样本大小更加有效的替代方法。看这篇文章,地球是平坦的(我想大概是与地球是圆的相对应的感觉)(P>0.05):意义阈值和不可复制的研究的危机。
" w0 k+ g# k8 W$ N9 K& D我承认,在我的科研生涯中我使用过我知道或者是感觉有严重缺陷的方法。还有就是,我承认已经教过——以及我一直在教——这种方法给我的学生。我有很多可疑的托辞,例如,因为这种方法构建了上世纪大部分的科学体系,我认为学生们应该知道它。
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 楼主| epiman 发表于 2018-6-21 17:27:55 | 显示全部楼层
2291175099 发表于 2018-6-21 16:35
4 g6 ]6 W  |* I8 `- D你好,我先给您看前两段的翻译(括号中添加的是我自己的想法,与文章翻译无关),若您觉得可以,我再继 ...
/ v, r/ N- {3 Y' w' Z5 N$ ?5 K" r
翻译的很好,我稍微修改了一下。请继续啊,不明白的地方,多揣摩一下原文,也可以贴出来请高手一起讨论。
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P-values and significance testing have come under increasing scrutiny in scientific research. How accurate are these methods for indicating whether a hypothesis is valid? PeerJ Author Valentin Amrhein looks at the many issues with significance testing, why the p-value may not be entirely to blame, and emerging alternatives aimed at addressing study design and sample size more effectively. See the research paper, The earth is flat (p > 0.05): significance thresholds and the crisis of unreplicable research., S/ m- P. L9 N  K
P值和显著性检验在科学研究中已经受到越来越多的审查(或者用推敲、研究?)。在表明假设是否成立时这些方法是如此精准?作者Valentin Amrhein看了许多我们无法用P值完全地解释的显著性检验的事例,以及新出现的目的是使得设计方案及样本大小更加有效的替代方法。看这篇文章,地球是平坦的(我想大概是与地球是圆的相对应的感觉)(P>0.05):意义阈值和不可复制的研究的危机。1 D, x; c" Y* r# E7 W5 L: D1 _2 E% A- N$ s
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under increasing scrutiny 受到越来越多的审视 更好一些。
% s0 c! `$ r& D, I& e9 F2 r7 |) b+ V4 T4 R* n6 [5 C" B
How accurate are these methods for indicating whether a hypothesis is valid? 在判断一个假设是否成立时这些方法的精确性如何?5 t( q! E' w) a/ z0 @
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PeerJ Author Valentin Amrhein looks at the many issues with significance testing, why the p-value may not be entirely to blame, and emerging alternatives aimed at addressing study design and sample size more effectively.  PeerJ杂志的作者Valentin Amrhein在察看了许多显著性检验、为何不能完全归咎于P值和旨在解决研究设计和样本量的新兴方法的专题。见论文:“地球是平的(P>0.05):显著性阈值和不可复制的研究的危机”。! }+ D# m" M, N* a, H6 C6 T- ~4 p6 ^7 Z

/ w9 g+ ]  I$ ^0 @I confess. Throughout my scientific life, I have used a method that I knew or felt was deeply flawed. What’s more, I admit to have taught — and I do still teach — this method to my students. I have a number of questionable excuses for that. For example, because the method has shaped a big part of science in the last century, I think students ought to know about it.3 r1 A1 e/ l6 t  x& O6 L6 W
6 V5 ^7 {# i+ X% y7 A' v
我承认,在我的科研生涯中我使用过我知道或者是感觉有严重缺陷的方法。还有就是,我承认已经教过——以及我一直在教——这种方法给我的学生。我有很多可疑的托辞,例如,因为这种方法构建了上世纪大部分的科学体系,我认为学生们应该知道它。
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2291175099 发表于 2018-7-7 23:30:52 | 显示全部楼层
epiman 发表于 2018-6-21 17:27
$ K  D! J/ {7 G2 ~, g( u翻译的很好,我稍微修改了一下。请继续啊,不明白的地方,多揣摩一下原文,也可以贴出来请高手一起讨论。 ...

( @* `7 o% p% }* ?不好意思,最近忙实习,今天才看到公卫人!
; C7 U+ I& @* C& i" ~" B谢谢你的回复,看了你的修改,感觉自己的翻译不够老练,还需要多多锻炼。
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 楼主| epiman 发表于 3 天前 | 显示全部楼层
飐舟渚月 发表于 2018-6-6 10:26: [- A" g( C1 Z
But I have increasingly come to believe that science was and is largely a story of success in spite  ...
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翻译得很好,有空继续翻译完这篇哈
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飐舟渚月 发表于 昨天 19:32 | 显示全部楼层
epiman 发表于 2018-12-8 21:34
2 b4 k5 e! R' I  Y: Y0 o翻译得很好,有空继续翻译完这篇哈

% |- i4 x: n" ~6 \好的 谢谢!
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飐舟渚月 发表于 昨天 19:36 | 显示全部楼层
You draw the conclusions/ X' ~4 L2 V, \% X
结论取决于你
- y. X& X$ E1 X; {Of course, everybody who thought that p-values are about null hypotheses, or even about alternative hypotheses, must now be disappointed. Yes, a small p-value can mean that the null hypothesis is false. But it can also mean that some mathematical aspect of the model was not correctly specified, or that we accidentally switched the names of some factor levels, or that we unintentionally — or intentionally — selected analyses that led to a small p-value (“p-hacking”), or that a cable was loose.0 ^% W$ C! @* t4 ?+ G' t
当然,那些说到p值只想着H0或是H1的人注定要失望了。一个小的p值能够说明H0假设错误,但是它也可能是因为模型中一些数学问题的规定不正确、人为不慎篡改了因素水平的设定、有意无意地选择了易于得到极小p值的算法(“篡改p值”),又或者是缆线松了。, s6 a( E/ C* S1 Y
Statistics cannot be inferential. It must be we who make the inference. As Boring (1919) put it one century ago: “Conclusions must ultimately be left to the scientific intuition of the experimenter and his public.”
: r, }9 _  z9 y. ^5 G统计学本身无法推断,能进行推断得出结论的是我们。正如Boring(1919年)在一个世纪前所说:“结论只能永远归于实验者及其追随者的科学直觉。”
" M7 V" O  O0 e8 R; {8 J0 M/ Y; hBut, interestingly, “one can feel widespread anxiety surrounding the exercise of informed personal judgment” (Gigerenzer 1993). People seem to mistrust inference by humans and to long for “objective” inferential decisions made by computer algorithms, based on data. And I can see there is a reason for this desire because, apparently, some human experts tend to make claims as part of their political agenda without bothering about data.9 p& F" m  o, y
但是,值得一提的是,“在进行具有充足依据的个人推断时,人们能感觉到无尽的焦虑。”(Gigerenzer 1993年)。人们似乎对人为得出的结论持有疑虑,并且期望由电脑对数据进行几何运算得到“客观公正的”推论。对这种期望,我有一个解释:一些专家更想把结论提上政治日程,并且免去对数据的担忧。
& O' H  y# v- O9 |: k( pOf course, personal judgment does not mean that anything goes. It means that if we have evidence that something could possibly be wrong with a model — if, for example, we found a small p-value — then we must apply informed personal judgment to try and find out what is wrong.* i3 L( g2 j. f8 s6 |
个人推断不是要指出哪一个是正确的,而是要说明有没有足够的证据指出模型中可能存在的错误,例如,在我们发现一个小的p值之后,我们一定要考虑周全以解释出错的原因。/ c- [# I1 s# v/ y9 h" x. m
The explanation may be that some alternative scientific hypothesis is correct, but there are many more things to consider. In the neutrinos-faster-than-light scenario outlined above, the explanation was neither to be found in the data nor in scientific theory, nor in statistics. My guess is that the correct inference was made by somebody applying scientific intuition or informed personal judgment when checking whether perhaps a cable was loose.
0 x3 n$ Q: ]. G8 g8 J解释可以说备择假设是正确的,但是还要考虑到更多其他的因素。上文提到的“中子运动快过光速”中,无论数据、科学理论或是统计结果都不足以解释p值,
$ H8 E; _7 c6 v$ ^; `) iBut don’t we do this all the time in our talks and papers: challenge our statistical results by discussing alternative explanations?
1 ]( Z4 I0 i. l/ n* w! E不过我们明明一直在论文和演讲中提到:要用其它解释来质疑已有的统计结果。
/ U/ H" V  O* N$ r6 N: G) WWell, there’s a lot to say about that. In biology, for example, which is my field of research, I rarely see papers by scientists who introduce and discuss their favored hypothesis only to conclude that their hypothesis seems to be wrong after all. In our discussion sections, it is usually the alternative explanations that are refuted./ {$ p7 ^, J1 g. W% c; w0 {) S# X
这其中的道理很深。比如在我所研究的生物学领域,我就很少看到有人引入讨论完要验证的假设,最后只得出“可能该假设不成立”的结论。在我们的讨论部分,往往驳斥的是另一种可能的假设。
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