Earlier quoted context omitted.
For starters, experimental bias isn't really an issue, here... This was an observational study, with crystal clear objective criteria for coding the dependent & independent variables. A cheap, simple observational study like this is merely a first step. No reasonable expert is claiming that this study proves anything worth making medical policy changes over. This study's sole purpose is to establish whether it's wort…
> experimental bias isn't really an issue, here... This was an observational study, with crystal clear objective criteria for coding the dependent & independent variables. I have no position on this particular study, but in general you can make your coding as simple and objective as you like and it won't do much about experimental bias. Objective processing of bad data isn't better than subjective processing of bad d…
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.