Closed lauramaxwell closed 1 month ago
Good call. Let's use dfMetrics$Type to pick the appropriate function instead of adding a new parameter
@jwildfire ok, so if Type %in% c("binary", "rate")
then we use Analyze_NormalApprox_PredictBounds
else if Type == "poisson"
we use Analyze_Poisson_PredictBounds
and any other value of Type we don't produce bounds since the other methods don't have a PredictBounds
function?
Expected Behavior
User should be able to control method for all steps used in their pipeline
Current Behavior
MakeBounds
hard codesAnalyze_NormalApprox_PredictBounds()
into the function, so poisson method cannot be used to calculatedfBounds
Possible Solution
Either we
MakeBounds()
to specify method and edit code toswitch
function based on this argument. this can be taken fromworkflow$meta
/dfMetrics
Model
param in workflows.NormalApprox
in all exampleschoice 1 is probably optimal, but wanted to make sure we still wanted to keep the other methods in general...
Steps to Reproduce
1. 4. 5. 6.
Context (Environment)
Possible Implementation
Additional Comments
Also need to add
Type
toreportingMetrics