Create a call to `mice::with.mids()` - r

Question

I am trying to create a call to mice::with.mids(), then evaluate it. It appears the call is being created, but then it cannot be evaluated (must be some environment/scoping issue?). I've created a pared down reproducible example below. Any assistance is greatly appreciated! Thank you!
mice_in_tbl_uvregression <-
function(data, # mice data of class mids
method, # regression method, eg. lm, glm
formula = "hp ~ mpg", # character formula (needs to be character for other reasons)
method.args = NULL # named list of other args that will be passed to `method=`
) {
# construct the call
fun_call <-
rlang::call2(
rlang::expr(with),
data = data,
expr = rlang::expr((!!method)(formula = !!as.formula(formula), !!!method.args))
)
# evaluate call
eval(fun_call)
}
set.seed(12345)
mice_in_tbl_uvregression(
data = mice::mice(mtcars, m = 2),
method = lm
)
#> Error in eval(predvars, data, env): object 'hp' not found
Created on 2021-06-27 by the reprex package (v2.0.0)

Answer 1

We could parse a string created (to extract the language call) before doing the evaluation
mice_in_tbl_uvregression <-
function(data, # mice data of class mids
method, # regression method, eg. lm, glm
formula = "hp ~ mpg", # character formula (needs to be character for other reasons)
method.args = NULL # named list of other args that will be passed to `method=`
) {
# construct the call
fun_call <- parse(text = glue::glue("with(data = {deparse(substitute(data))}, expr = {deparse(substitute(method))}(as.formula({formula})))"))
print(fun_call[[1]])
out <- eval(fun_call)
out$call$expr[[2]] <- out$call$expr[[2]][[2]]
out
}
-testing
set.seed(12345)
out1 <- mice_in_tbl_uvregression(
data = mice::mice(mtcars, m = 2),
method = lm
)
-output
out1
call :
with.mids(data = mice::mice(mtcars, m = 2), expr = lm(hp ~ mpg))
call1 :
mice::mice(data = mtcars, m = 2)
nmis :
mpg cyl disp hp drat wt qsec vs am gear carb
0 0 0 0 0 0 0 0 0 0 0
analyses :
[[1]]
Call:
lm(formula = as.formula(hp ~ mpg))
Coefficients:
(Intercept) mpg
324.08 -8.83
[[2]]
Call:
lm(formula = as.formula(hp ~ mpg))
Coefficients:
(Intercept) mpg
324.08 -8.83