add make_dummy_vars argument

[malcolmbarrett]

Closes #6

@LucyMcGowan, what do you think? Do regression-style dummy variables make sense, or should there be a dummy variable for every level? e.g. education1 is not included here because it's the comparison/base level

library(tidysmd)

plot_df <- tidy_smd(
  nhefs_weights,
  c(age, race, education),
  .group = qsmk,
  .wts = w_ate
)

love_plot(plot_df)

plot_df_dummies <- tidy_smd(
  nhefs_weights,
  c(age, race, education),
  .group = qsmk,
  .wts = w_ate,
  dummy_variable = TRUE
)

love_plot(plot_df_dummies)

^{Created on 2022-08-12 by the reprex package (v2.0.1)}

[LucyMcGowan]

This looks awesome. I am trying to think about the argument name since it is likely to update multiple variables? So something like make_dummy or just dummy? (Maybe this is silly!)

[LucyMcGowan]

Patrick laughed out loud at make_dummy so maybe not 🙃

[malcolmbarrett]

Haha maybe ‘make_dummy_vars’. I like a verb here because the original name sort of sounds like it should be the names of dummy variables.

To confirm, you’re okay with these contrasts? E.g. that there’s no education1 (as there wouldn’t be in regression)?

[LucyMcGowan]

Yes! I think that makes sense. The referent is the same as would be picked from a model?

[malcolmbarrett]

Right, it uses model.matrix() to create them, as do lm() and friends. Likewise, you can change the reference group the same was as in a model:

library(tidysmd)

# make "graduated high school" the reference group
nhefs_weights$education <- relevel(nhefs_weights$education, ref = "3")
  
plot_df_dummies <- tidy_smd(
  nhefs_weights,
  c(age, race, education),
  .group = qsmk,
  .wts = w_ate,
  make_dummy_vars = TRUE
)

love_plot(plot_df_dummies)

^{Created on 2022-08-13 by the reprex package (v2.0.1)}