4 ms·

All studies have some level of risk for bias... But that doesn't mean all studies have the same level of risk. The essay you linked is very good, but it's actu

All studies have some level of risk for bias... But that doesn't mean all studies have the same level of risk. 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.

jimbojet 5y ago
You sound like you just took a stats 101 class and now are bragging to a bunch of adults about how much you learned in stats 101. Sincerely, someone working in the field for last 7 years.
- SkittyDog 5y ago
  Sounds like I don't know nearly as as you... I minored in stats 20+ years ago, but since then I do a lot more arguing about stats than actually using them for work. 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.
thaumasiotes 5y ago
> 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. 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.

jimbojet 5y ago

You sound like you just took a stats 101 class and now are bragging to a bunch of adults about how much you learned in stats 101. Sincerely, someone working in the field for last 7 years.

SkittyDog 5y ago
Sounds like I don't know nearly as as you... I minored in stats 20+ years ago, but since then I do a lot more arguing about stats than actually using them for work. 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.

thaumasiotes 5y ago

> 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. 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.