Malcolm Barrett
Malcolm Barrett
Improve documentation for `part_pc1()` and allow `reduce_first_component()` to operate independently
Thanks for confirming and for both of your input. I'll try to address this soon now that it's clearer in my mind
Improve documentation for `part_pc1()` and allow `reduce_first_component()` to operate independently
#41 should address this. I'll try to get this on CRAN this week ``` r library(partition) set.seed(1234) df Director: Minimum Distance (Pearson) #> Metric: Intraclass Correlation #> Reducer: First Principal...
Improve documentation for `part_pc1()` and allow `reduce_first_component()` to operate independently
On its way to CRAN
ggdag expects this, so I'd need to know if it was changed, but I agree. It's not clear at all, and even I forget that that's what it means.
Trimming example where you look at who got trimmed, pre trimming as target trial exclusion criteria
No, I'm going to rework this chapter to show a simpler approach you can use when it's a pre-post analysis (cloning and standardizing). We're going to use the currently described...
This may already be fixed in the development version if memory serves correctly. Could you try installing the version on GitHub (see `README` if you need instructions) and reporting back?
Confirmed this is still the case in dev
This is specifically a bug in `as_tidy_dagitty.data.frame()`. Other methods work correctly: ``` r library(ggdag, warn.conflicts = FALSE) dag tidy_dagitty() dag$data #> # A tibble: 4 × 8 #> name x...
I said earlier this was still the case in dev but I actually can't replicate it now. Could you try again? ```r > library(ggdag) dag % as_tidy_dagitty() print(dag$data) print(dag$dag) #...