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Write event-study results to a Stata .dta file

Source: R/nabs_dta.R
nabs_write_dta.Rd

`nabs_write_dta()` exports an `nabs_event_study_tbl` – or anything that [as_nabs_event_study()] can coerce into one, including the result objects returned by [nabs_event_study()] and [nabs_event_study_simple()] – to a Stata `.dta` file via [haven::write_dta()].

Usage

nabs_write_dta(x, path, version = 14, label = NULL, verbose = TRUE)

Arguments

x

An `nabs_event_study_tbl`, an `nabs_event_study_result`, an `nabs_event_study_simple`, a supported estimator object, or a plain data frame with at least `time` and `estimate` columns. Anything that is not already a data frame is routed through [as_nabs_event_study()].

path

Path of the `.dta` file to write.

version

Stata file format version, passed to [haven::write_dta()]. Default `14` (readable by Stata 14 and later).

label

Optional dataset label (Stata's `label data`), passed to [haven::write_dta()].

verbose

Logical; if `TRUE` (default), print a one-line summary including any column renames.

Value

The path, invisibly.

Details

The tidy schema uses dots in some column names (`std.error`, `conf.low`, `conf.high`), which are not valid Stata variable names. These are renamed to underscore versions (`std_error`, `conf_low`, `conf_high`) on the way out; any other invalid characters are likewise replaced with `_`.

This makes the "estimate in R, post-process in Stata" workflow a one-liner: a Stata-using coauthor can rebuild the event-study figure with `twoway rcap`/`scatter`, or feed the estimates into their own tables.

See also

[nabs_read_dta()] for the reverse direction.

Examples

if (requireNamespace("haven", quietly = TRUE)) {
  tidy <- as_nabs_event_study(
    data.frame(time = -2:3,
               estimate = c(0.02, -0.01, 0, 0.4, 0.5, 0.45),
               std.error = 0.1),
    method = "DCDH", outcome = "y"
  )
  tmp <- tempfile(fileext = ".dta")
  nabs_write_dta(tidy, tmp)

  haven::read_dta(tmp)
}
#> Wrote 6 rows to /tmp/RtmpMuwHfR/file1ebf2c08c61.dta (Stata version 14).
#> ℹ Renamed for Stata: std.error -> std_error, conf.low -> conf_low, conf.high ->
#>   conf_high.
#> # A tibble: 6 × 8
#>    time estimate std_error conf_low conf_high window method outcome
#>   <dbl>    <dbl>     <dbl>    <dbl>     <dbl> <chr>  <chr>  <chr>  
#> 1    -2     0.02       0.1   -0.176     0.216 pre    DCDH   y      
#> 2    -1    -0.01       0.1   -0.206     0.186 pre    DCDH   y      
#> 3     0     0          0.1   -0.196     0.196 post   DCDH   y      
#> 4     1     0.4        0.1    0.204     0.596 post   DCDH   y      
#> 5     2     0.5        0.1    0.304     0.696 post   DCDH   y      
#> 6     3     0.45       0.1    0.254     0.646 post   DCDH   y