To your second point, I alway go back to this quote: "You can't fix by analysis what you bungled by design" (Light, Singer and Willett, 1990).
If a paper is broken by design, there isn't much to do after the fact. It's just broken.
The problem is that doing a good RCT takes both time and effort, with the huge risk of having null results, which usually results in a desk rejection from most top journals.
So, you either are a top-fund raising researcher who can both fund multiple RCTs and people to support them, or you just try your best with what you have and hope to squeeze a paper out from you did.
Releasing the data won't really help much if the data generating process is flawed. Sure, other people will be able to run different kind of analyses (e.g., jackknife your standard errors instead of just using a robust correction), but I'm not sure how helpful that will be.
A third issue that I have also encountered is that journal editors have an agenda when putting together an issue, which sometimes overwrites the "quality' of the research with "fit" to the issue. This could lead to "lower quality" articles to be published because they fit the (often unspoken) direction of the journal. Most editors see their role as steering the field towards new directions (a sort of a meta service to the field) and sometimes that comes at the expense of the quality of the work.
> Releasing the data won't really help much if the data generating process is flawed. Sure, other people will be able to run different kind of analyses (e.g., jackknife your standard errors instead of just using a robust correction), but I'm not sure how helpful that will be.
It allows motivated people to catch more subtle forms of nonsense. Data colada, for example, has caught outright fraud, but only through herculean efforts. Imagine what groups like this might do if they had the raw data.
A citation like the one above should normally point to a full reference in a bibliography section. Did you forget the \bibliography{} command at the end of your comment?
If a paper is broken by design, there isn't much to do after the fact. It's just broken.
The problem is that doing a good RCT takes both time and effort, with the huge risk of having null results, which usually results in a desk rejection from most top journals.
So, you either are a top-fund raising researcher who can both fund multiple RCTs and people to support them, or you just try your best with what you have and hope to squeeze a paper out from you did.
Releasing the data won't really help much if the data generating process is flawed. Sure, other people will be able to run different kind of analyses (e.g., jackknife your standard errors instead of just using a robust correction), but I'm not sure how helpful that will be.
A third issue that I have also encountered is that journal editors have an agenda when putting together an issue, which sometimes overwrites the "quality' of the research with "fit" to the issue. This could lead to "lower quality" articles to be published because they fit the (often unspoken) direction of the journal. Most editors see their role as steering the field towards new directions (a sort of a meta service to the field) and sometimes that comes at the expense of the quality of the work.