If any dan-level statistician here has the inclination, I'll post a link to the paper here for your perusal...
Is there any reason not to post the link immediately? You are creating an additional barrier (pretty steep one) that lessens your chances of getting any cooperation.
Well, I was only going to post all the minutiae if there was any interest...
http://jama.ama-assn.org/cgi/reprint/295/3/285.pdf
The two groups are as follows:
Assigned to "Watchful Waiting":
Assigned to surgery:
Some patients crossed between the two groups, but this does not matter, as they were testing the effects of the initial assignment.
They report p = 0.52, but they also give a 95% confidence interval for the difference in risk, which just barely contains zero; which is a dead giveaway that p should be around 0.05, right? Anyway, doing a chi-squared test on the above numbers, I got p = 0.053.
The relevant bit is at the top of page 289 (page 6 of the PDF). Also relevant are the Results section of the abstract, and Figures 1 and 2. Essentially the entire problem is this statement:
At 2 years, intention-to-treat analyses showed that pain interfering with activities developed in similar proportions in both groups (5.1% for watchful waiting vs 2.2% for surgical repair; difference 2.86%; 95% confidence interval, -0.04% to 5.77%; P=.52)
I recently had to have some minor surgery. However, there's a body of thought that says it's safe to wait and watch for symptoms, and only have surgery later. There's a peer reviewed (I assume) paper supporting this position.
Upon reading this paper I found what looked like a statistical error. Looking at outcomes between two groups, they report p = 0.52, but doing the sums myself I got p = 0.053. For this reason, I went and had the surgery.
Since I'm just a novice at statistics, I was wondering if I had in fact got it right - it's disturbing to think that a peer reviewed paper stating an important conclusion would be wrong.
If any dan-level statistician here has the inclination, I'll post a link to the paper here for your perusal...
Parapsychologists make a poor control group of scientists because part of their job is collecting evidence that parapsychology works. In science, that step is already done. Biologists do not need to prove that life works, because life exists. Physicists do not need to prove that physics works, because physics, by definition, IS the way the universe works. Einstein did not dream up relativity and then start looking for evidence to support it. He looked at the evidence that was available, and came up with relativity as a way to explain it. Parapsychologists do it the other way around.
In science, that step is already done.
Only in general, but not for specific questions like: does compound XYZ affect tumour growth?
And with the number of fake researchers apparently staying roughly even for a period of fifty years, looking from the way the effect size hasn't changed?
That right there is a really good point I didn't think of. As for motive, my impression is that a lot of parapsychologists are trying to demonstrate the truth of beliefs that are incredibly significant to them-- their new age spirituality is at stake. For that matter, if they've dedicated their lives to the subject. If there are no psychic phenomena they have literally spent their lives studying nothing. You might as well ask why theologians never come up with arguments disproving the existence of God. But your point about consistency makes this all moot. I'll check out the book.
why theologians never come up with arguments disproving the existence of God
Well if they do they get called philosophers of religion instead...
In no way do I think that the parapsychologists have good hypotheses or reasonable claims. I also am a firm adherent to the ethos: Extraordinary claims must have extraordinary proofs. However to state the following:
one in which the null hypothesis is always true.
is making a bold statement about your level of knowledge. You are going so far as to say that there is no possible way that there are hypotheses which have yet to be described which could be understood through the methodology of this particular subgroup. This exercise seems to me to be rejecting these studies intuitively,(without study) just from the ad hominem approach to rejection - well they are parapsychologists therefore they are wrong. If they are wrong, then proper analysis would indicate that, would it not?
I have never seen a parapsychology study, so I will go look for one. However does every single study have massive flaws in it?
However to state the following: "one in which the null hypothesis is always true" is making a bold statement about your level of knowledge.
OK. But the point about what we can conclude about regular science stands even if this is only mostly correct.
Parapsychologists are constantly protesting that they are playing by all the standard scientific rules, and yet their results are being ignored - that they are unfairly being held to higher standards than everyone else. I'm willing to believe that. It just means that the standard statistical methods of science are so weak and flawed as to permit a field of study to sustain itself in the complete absence of any subject matter.
— Eliezer Yudkowsky, Frequentist Statistics are Frequently Subjective
Imagine if, way back at the start of the scientific enterprise, someone had said, "What we really need is a control group for science - people who will behave exactly like scientists, doing experiments, publishing journals, and so on, but whose field of study is completely empty: one in which the null hypothesis is always true.
"That way, we'll be able to gauge the effect of publication bias, experimental error, misuse of statistics, data fraud, and so on, which will help us understand how serious such problems are in the real scientific literature."
Isn't that a great idea?
By an accident of historical chance, we actually have exactly such a control group, namely parapsychologists: people who study extra-sensory perception, telepathy, precognition, and so on.
I really like the idea of parapsychology as the control group for science; it deserves to be better known.
In a symmetric war, not targeting civilians is cooperating in an iterated prisoner's dilemma; you don't want to switch from C/C, except in the (seemingly very unlikely) event that the war will end so much more quickly that overall suffering is reduced.
What you say seems correct as a matter of pure terminal values, but this also seems like a great example of a situation where common-sense values that claim to be terminal* are implausible as such but contain real instrumental wisdom.
* to the incomplete extent that common-sense morality makes this distinction
In a symmetric war
True, but these are pretty rare these days.
Correct.
EDIT: If I were picking nits, I would say, "'Should' does apply to paperclip maximizers - it is rational for X to make paperclips but it should not do so - however, paperclip maximizers don't care and so it is pointless to talk about what they should do." But the overall intent of the statement is correct - I disagree with its intent in neither anticipation nor morals - and in such cases I usually just say "Correct". In this case I suppose that wasn't the best policy, but it is my usual policy.
Of course, Kant distinguished between two different meanings of "should": the hypothetical and the categorical.
This seems useful here...
= f037147d6e6c911a85753b9abdedda8d){kind=logo}
= 27d567bc2d48d9f40e9ccc20ea370b15)
= b715d02e85f7b3b4ae65ca3d3e450868)
Subscribe to RSS Feed
It matters to your case. I refuse to believe that writing a patient's name on this list rather than that list has a direct causal influence upon their state in 2 years. The influence can only proceed via their actual treatment.
The decision facing you is whether to have surgery early or not. That is the thing whose effect on the outcome you want to know. To the extent that in the study this differs from the initial assignment, the study is diminished; therefore it should matter to the people conducting the study also.
I see from the paper that 23% of those assigned to Watchful Waiting nevertheless had surgery within 2 years, and 17% of those assigned to surgery did not have surgery in 2 years. (Some others died of unrelated causes or left the study early.)
I'll leave it to a dan-grade statistician to judge how to obtain the best conclusion from these data.
But the question is whether it's safe to advise people to wait, knowing that they can have surgery later if needed.
Anyway my main question was whether I'd done the stats right.