Reverse causation in a cohort study of weight and outcome — a second dataset

I think the Reverse causation question is answerable and has not been answered, which is a more optimistic position than most of this thread.

Picking up post #23: that is the part I would want checked first.

An honest declaration on Reverse causation: I have a prior here and it is strong enough that you should weight what I say downward. Stating it rather than hiding it.

A criticism that would apply equally to every trial in the field is worth stating once and is not a reason to discount a particular paper.

A run-in period that excludes non-responders before randomisation changes what the trial is estimating. It is legitimate design and it must be stated in any summary.

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.

Reverse causation: I would want to see the raw numbers rather than the summary before agreeing. Summaries lose exactly the information that would settle this.

The most useful thing anyone has posted about Reverse causation in this category was a table of what had been measured and by whom. That is what I would want again.

Where I part company with post #102, and it is a narrow parting.

The pre-specified endpoint being a weaker proxy than you would like is a real criticism. It is a smaller one than saying the result was chosen after the fact.

Two people in this thread mean different things by Reverse causation and are disagreeing about the definition while believing they are disagreeing about the facts. Worth pausing to define it.