> But this SSRI/COVID study isn't doing that. They're literally just looking at patient records, and counting hospitalization vs current SSRI usage. They're not picking up mice to count ticks... They're exporting records to a spreadsheet, and summing columns.
> Now, these guys might have problems with the quality of the records they're relying on... Who knows whether the records are accurate or not. But that's a problem of data quality, not experimental bias.
Well, no, I have to disagree with this analysis. The mouse study described in that essay didn't run into bias problems, and the reason it didn't is that it was counting the ticks itself. But other tick-counting studies did have bias problems (due to bad methodology), and the Lyme-disease studies based on the bad tick-counting studies had the same bias problems (because they were using the bad data). The bias doesn't go away when you wash it through two publications instead of one. It's not a different kind of problem -- or even a different instance of the same kind of problem! -- and there's no reason to give it a different name.
You're kinda right about one thing, though... I am definitely talking down to OP, and a couple of other folks.
I'm frustrated. There are real problems in how science uses statistics, and it sounds like OP & co have heard about those problems. But the way they talk about this study, they're just throwing crap against the wall to have something to say. They don't really seem to understand the problems they're talking about, or how those problems apply to the study we're currently talking about.
I should change my attitude, and stop taking out my frustrations on these folks. If they're wrong, I'm probably not going to change their minds by insulting them.
The essay you linked is very good, but it's actually illustrating my point... The mouse study ran into bias problems because they had to go and directly measure something in nature, and then turn that into a number. That introduces several opportunities for error.
But this SSRI/COVID study isn't doing that. They're literally just looking at patient records, and counting hospitalization vs current SSRI usage. They're not picking up mice to count ticks... They're exporting records to a spreadsheet, and summing columns.
Now, these guys might have problems with the quality of the records they're relying on... Who knows whether the records are accurate or not. But that's a problem of data quality, not experimental bias.
You might say "Who cares? Either kind of error undermines the results, just the same!" But it definitely suggests that the other guy doesn't know what he's talking about... Because if he did understand stats, he would have used the right terminology.