Chronology is evidence of causality, but it’s weak evidence. In this case, there are (at least) two problems. First, there could be some other factor (disruption of social network? increase in pro-inflamatory microbiota?) which causes both, but the sex is caused faster. Alternatively, it could be that depression causes low sex drive, but that kicks in immediately whereas it takes months to get a depression diagnosis.
There are good ways to determine causality from observational data, but timing isn’t one of them.
Hm? What Pisani is pointing out here is that of the 3 major causal patterns that a cross-sectional correlation can reflect, A->B, B->A and A<-C->B, a longitudinal correlation in which observations of A are followed by observations of B, will let you rule out 1 of the 3 patterns (B->A), reverse causation, which leaves either the hypothesized direct causation or confounding. This is much better evidence than just the cross-sectional approach, although I think confounding is much more likely in general so the boost is not as big as the trichotomy makes it sound.
Reverse causation is not ruled out because diagnosis can be delayed.
It seems entirely plausible to me that it takes several months of worsening depression symptoms (during which time sex drive is effected) before a patient sees a psychiatrist.
I suppose it’s ruled out if we separate “depression” and “diagnosed with depression” into separate nodes, but that doesn’t rule out anything interesting.
Chronology is evidence of causality, but it’s weak evidence. In this case, there are (at least) two problems. First, there could be some other factor (disruption of social network? increase in pro-inflamatory microbiota?) which causes both, but the sex is caused faster. Alternatively, it could be that depression causes low sex drive, but that kicks in immediately whereas it takes months to get a depression diagnosis.
There are good ways to determine causality from observational data, but timing isn’t one of them.
Hm? What Pisani is pointing out here is that of the 3 major causal patterns that a cross-sectional correlation can reflect, A->B, B->A and A<-C->B, a longitudinal correlation in which observations of A are followed by observations of B, will let you rule out 1 of the 3 patterns (B->A), reverse causation, which leaves either the hypothesized direct causation or confounding. This is much better evidence than just the cross-sectional approach, although I think confounding is much more likely in general so the boost is not as big as the trichotomy makes it sound.
Reverse causation is not ruled out because diagnosis can be delayed.
It seems entirely plausible to me that it takes several months of worsening depression symptoms (during which time sex drive is effected) before a patient sees a psychiatrist.
I suppose it’s ruled out if we separate “depression” and “diagnosed with depression” into separate nodes, but that doesn’t rule out anything interesting.