I've noticed a strange issue with the check_assumptions() function. Check_assumptions() should return one (!) ggplot-object with four panels. During recent use however two ggplot-objects are returned with two panels each. This happens for lms, gams, etc.
I'm not sure why this is happening as the code seems fine. I assume it is an issue with how we add the individual plot objects together. Both ggpubr::ggarrange(rr0, rr1, rr2, rr3, nrow=2) and ggpubr::ggarrange(plotlist = list(rr0, rr1, rr2, rr3), nrow=2) have the same issue.
I have also found a workaround: instead of ggpubr::ggarrange(rr0, rr1, rr2, rr3, nrow=2) use ggpubr::ggarrange(rr0, rr1, rr2, rr3, nrow=2, ncol = 2).
I'll commit the changes to the code later but still this is strange behaviour as nrow = 2 should do the trick...
I've noticed a strange issue with the check_assumptions() function. Check_assumptions() should return one (!) ggplot-object with four panels. During recent use however two ggplot-objects are returned with two panels each. This happens for lms, gams, etc.
I'm not sure why this is happening as the code seems fine. I assume it is an issue with how we add the individual plot objects together. Both ggpubr::ggarrange(rr0, rr1, rr2, rr3, nrow=2) and ggpubr::ggarrange(plotlist = list(rr0, rr1, rr2, rr3), nrow=2) have the same issue.
I have also found a workaround: instead of
ggpubr::ggarrange(rr0, rr1, rr2, rr3, nrow=2)
useggpubr::ggarrange(rr0, rr1, rr2, rr3, nrow=2, ncol = 2)
.I'll commit the changes to the code later but still this is strange behaviour as nrow = 2 should do the trick...