I am not sure I am looking at the same table as you… Are you seriously arguing that in Table 2, which is used to show heterogeneous treatment effects, that the appearance of heterogeneity is just an artifact of small sample size, and moreover, you can somehow infer that the true conditional odds ratio is 4.5 in both strata? Where does the number 4.5 even come from?
This is not what Frank was arguing. He was arguing that even if there is true treatment effect heterogeneity, the bias due to omitting the interaction term may be less problematic than the loss of precision from including the interaction parameter. I am not fully sold on that argument, but this is a fairly standard view in statistics which a reasonable person might argue for. I am genuinely confused about how someone would think this means that any apparent differences between strata have to be an artifact…
My personal view is that trading off bias for precision is “cheating” and gives you uninterpretable inferential statistics. In my opinion, the correct move is to accept that the standard errors will be large unless we can increase sample size. I would rather have an honest but imprecise prediction. But that is an argument for another day, and not really related to this thread