Could someone explain the reasoning behind choosing the dependent trait in pairwise logistic regression of two categorical traits. My hypothesis does not explicitly state which trait is the IV as I just need the relationship between traits. To word this another way, I dont understand theoretically why the directioning in the model is important.

I have ~100 traits of a binary (presence/absence) type and am running pairwise logistic regressions on each trait combination using an R package that fits phylogeny as a covariant.

Code:

`phyloglm(trait[,i]~trait[,j], data=datafile, phy=treedata, method = c("MPLE","IG10"))`

Code:

```
logreg$loglik
[1] -6.276559
```

Code:

```
logreg$loglik
[1] -67.33166
```

My overall plan is to compare the divergence of a phylogenetic model with a standard logistic regression (subtract log likelihoods), but need to understand why swapping the model around gives different results first.

I would appreciate any suggestions here.

Cheers,

Lesley