tidy.mipo(x, ...) passes ... to summary(x, ...)

[vincentarelbundock]

This PR changes 2 lines of code.

Motivation: It would often be useful for tidy.mipo to pass ... to summary. For example, to use the exponentiate=TRUE option in logistic regression:

    library(mice)
    library(tidyverse)
    data("toenail2")

    xdata <- tidyr::complete(toenail2, patientID, visit) %>%
      tidyr::fill(treatment) %>%
      dplyr::select(-time) %>%
      dplyr::mutate(patientID = as.integer(patientID))

    z1imp <- mice(xdata, method = "pmm", maxit = 1, m = 5, seed = 1)
    z1model <- with(z1imp, glm(outcome ~ treatment, binomial))
    z1model.pool <- pool(z1model)

    tidy(z1model.pool)
    #>                   term   estimate  std.error  statistic   p.value            b
    #> 1          (Intercept) -1.2671348 0.07899231 -16.041242 0.0000000 0.0004436482
    #> 2 treatmentterbinafine -0.1558574 0.11681645  -1.334208 0.1835811 0.0014746179
    #>         df dfcom        fmi     lambda m        riv        ubar
    #> 1 425.1451  2056 0.08959265 0.08531989 5 0.09327839 0.005707408
    #> 2 209.9417  2056 0.13784827 0.12967396 5 0.14899469 0.011876541

    tidy(z1model.pool, exponentiate=TRUE)
    #>                   term  estimate  std.error  statistic   p.value            b
    #> 1          (Intercept) 0.2816374 0.07899231 -16.041242 0.0000000 0.0004436482
    #> 2 treatmentterbinafine 0.8556812 0.11681645  -1.334208 0.1835811 0.0014746179
    #>         df dfcom        fmi     lambda m        riv        ubar
    #> 1 425.1451  2056 0.08959265 0.08531989 5 0.09327839 0.005707408
    #> 2 209.9417  2056 0.13784827 0.12967396 5 0.14899469 0.011876541

[stefvanbuuren]

Useful extension. Thanks.

[mcomsa]

Thank you so much for the change. Now estimates are exponentiated, but standard errors are not. Please, see the same example.

[vincentarelbundock]

@mcomsa this is broom issue. Please see my reproducible example in the linked issue.