felm doesn't work with broom::augment/purrr but works with tidy

Question

I'm trying to run regressions within a nested data frame as described here. For my purposes, I'm using felm from the lfe package because I have many levels of fixed effects.

If I re-do the example in the link above using felm instead of lm, it works for the most part until I try to use broom::augment.

library(tidyverse)
library(broom)
library(gapminder)
library(lfe)

by_country <- gapminder %>% 
  group_by(continent, country) %>% 
  nest()

country_felm <- function(data){
  felm(lifeExp ~ year, data = data)
}

by_country <- by_country %>% 
    mutate(model = purrr::map(data, country_felm)
    )

Everything works up to this point except that I had to use a function instead of a formula in purrr::map in the last line of code, possibly another felm quirk.

Now if I try to use broom to extract the model output, it works for glance and tidy, but not for augment.

by_country %>% unnest(model %>% purrr::map(broom::glance))
by_country %>% unnest(model %>% purrr::map(broom::tidy))
by_country %>% unnest(model %>% purrr::map(broom::augment))

Trying to use augment results in the following error message:

Error in mutate_impl(.data, dots) : 
  argument must be coercible to non-negative integer
In addition: Warning message:
In seq_len(nrow(x)) : first element used of 'length.out' argument

score 1 · Accepted Answer · answered Mar 07 '17 at 19:16

It looks like augment is having trouble finding the data for the data argument, which is generally the dataset used for fitting.

The problem is easier to see if working with a single one of these models rather than all of them at once.

This doesn't work, with your given error:

augment(by_country$model[[1]])

But explicitly passing the data to the data argument does:

augment(by_country$model[[1]], data = by_country$data[[1]])

A work-around is therefore to pass the dataset to augment as the second argument. This can be done via purrr:map2, looping through both the model and data columns at the same time.

by_country %>%
    unnest(model %>% purrr::map2(., data, augment))

felm doesn't work with broom::augment/purrr but works with tidy

1 Answers1