DeclareDesign
lh_robust does not work with multiple outcomes
lho <- lh_robust(cbind(mpg, am) ~ cyl + gear, data = mtcars, linear_hypothesis = c("cyl = 2", "cyl = gear"))
Output:
Error in constants(lhs, cnames_symb) :
The hypothesis "cyl = 2" is not well formed: contains bad coefficient/variable names.
In addition: Warning message:
In constants(lhs, cnames_symb) : NAs introduced by coercion
car has a seperate method for mlm, you might be able to get this working by fiddling with the classes of the output object that lm_robust is producing.
On Mon, Mar 4, 2019 at 9:05 PM Luke Sonnet [email protected] wrote:
lho <- lh_robust(cbind(mpg, am) ~ cyl + gear, data = mtcars, linear_hypothesis = c("cyl = 2", "cyl = gear")) Output:
Error in constants(lhs, cnames_symb) : The hypothesis "cyl = 2" is not well formed: contains bad coefficient/variable names. In addition: Warning message: In constants(lhs, cnames_symb) : NAs introduced by coercion
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method for mlm performs tests but doesn't compute variance or expected value of the linear combination of coefficients, so not so sure what would we include in the tidy output.
:(
We may be able to decompose an mlm into a list of lm, but that seems a bit painful.
Any advice here? I don't think we can very easily accommodate this and believe we should explicitly fail to support this with a message, while just returning the usual lm_robust() output.
I think this should be an error that says you have to go outcome by outcome
Anyone have any feelings re: error? I think that's also reasonable. I'll implement it as such later today/tomorrow if no other feedback.