Yeap, one small scale meta data analysis isn’t going to be able to prove causality. Plus, the analysis was done by a researcher who’s been actively participating in a lawsuit against the makers of Tylenol.
The problem with using meta data analysis is they struggle with causation vs correlation. As you suggested, it could have to do with fevers. Or it could simply be that mothers who have high quality access to gynecological services and prenatal care good enough to study umbilical samples also have greater access to diagnose their children with autism later in life.
Large scale metadata analysis can provide us with information we can use to hone in on what to study in greater depth. Small scale metadata analysis imo aren’t’ very useful in any meaningful way, and are more often than not used to subjectively validate claims to the scientifically illiterate majority.
Yeap, one small scale meta data analysis isn’t going to be able to prove causality. Plus, the analysis was done by a researcher who’s been actively participating in a lawsuit against the makers of Tylenol.
The problem with using meta data analysis is they struggle with causation vs correlation. As you suggested, it could have to do with fevers. Or it could simply be that mothers who have high quality access to gynecological services and prenatal care good enough to study umbilical samples also have greater access to diagnose their children with autism later in life.
Large scale metadata analysis can provide us with information we can use to hone in on what to study in greater depth. Small scale metadata analysis imo aren’t’ very useful in any meaningful way, and are more often than not used to subjectively validate claims to the scientifically illiterate majority.