This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1.
Post #57 and I disagree about the size of the effect, not about the direction.
Marking my uncertainty on Reverse causation explicitly. I am confident about the direction, much less confident about the size, and not confident at all that it generalises past the case in the first post.
Taking Reverse causation seriously for a moment rather than deflecting: the honest position is that the community has observations and no controlled comparison, and those two things support very different sentences.
Surrogate endpoints are not automatically bad and their validity is compound-specific and population-specific. The question is whether this surrogate has been validated for this use.
I have said this before in a thread nobody could find, so it is worth repeating.
If someone has run Reverse causation properly I would rather read that than my own reconstruction of it. Posting mine only because the thread has gone quiet.
Reading back through the Reverse causation threads from last year, the same three questions come up every time and only one of them has ever been answered properly. That seems like a documentation gap rather than a knowledge gap.
Generalisability: do the inclusion/exclusion criteria narrow the population so much that results do not apply to real people asking about it? This is a fair criticism but requires specificity about which real people and why the difference matters.
I have no interest in any supplier named above.
That is clearer than the version I had in my head. Thank you.
Hold a trial to the standard something could actually have met. A criticism that no achievable design could have answered is a criticism of the field rather than of the paper.
I am confident about the direction and much less about the magnitude.
Picking up post #69: that is the part I would want checked first.
On Reverse causation: the maintained page in the documentation commons covers the general case with citations and a review date, which is more reliable than any reply here including this one.
The documentation on Reverse causation is better than this thread and I say that as someone who has posted in the thread.
Post #72 is right about the mechanism and I think understates the practical bit.
The bit of Reverse causation that nobody enjoys is that the answer changes depending on what you are trying to decide with it. Say what the decision is and the thread will converge.
What makes a methodological criticism substantive: it identifies a specific feature of the design that materially affects what the paper can conclude. "Small sample size" alone is weak. "Small sample size for a rare outcome, so the confidence interval is wide" is stronger.
I checked the source rather than the summary, and they differ.
Adding what did not work for me on Reverse causation, since the failures never get written up and they are half the useful information.
Clear enough that I do not think I have a follow-up, which is unusual.
Post #75 answers the question as asked. The question underneath it is different.
The claim about Reverse causation upthread is stronger than its source supports. I have read the source. The source says "associated with" and the post says "causes".
I read post #74 twice before replying, because I had assumed the opposite.
Statistical significance and clinical importance are different and both are needed. A significant difference below the minimal important difference is a real finding of no practical consequence.
The arithmetic in post #77 is right; the assumption feeding it is the part to check.
My position on Reverse causation is current rather than settled. I have revised it once already and I expect to again, so treat it accordingly.
Surrogate endpoints are not automatically bad and their validity is compound-specific and population-specific. The question is whether this surrogate has been validated for this use.
The conclusion is tentative; the arithmetic underneath it is not.
Post #79 is the version of this I will quote in future. One addition.
Per-protocol and intention-to-treat analyses answer different questions and neither is the honest one by default. Reporting both is the practice worth insisting on.
A qualification I should have led with rather than closed on.
An observation about Reverse causation that I cannot explain and am posting anyway, on the principle that unexplained observations are more useful public than private.
Post #83 put the caveat in the right place and I want to underline it.
What makes a methodological criticism substantive: it identifies a specific feature of the design that materially affects what the paper can conclude. "Small sample size" alone is weak. "Small sample size for a rare outcome, so the confidence interval is wide" is stronger.
That is the shape of it. The detail is where I would expect to be corrected.
Building on post #83 rather than restating it.
The reason Reverse causation is hard to answer is that the obvious measurement and the relevant quantity are not the same thing, and substituting one for the other is silent.
Appreciated. The plain phrasing does more work here than a longer post would.
Practical experience of Reverse causation, offered as one case with the conditions stated, not as a general finding. Conditions first, because they are what make it interpretable.