reverse_map_total_n() takes the output of a function created
by function_map_total_n() and reconstructs the original data frame.
See audit_total_n(), which takes reverse_map_total_n() as a basis.
Value
The reconstructed tibble (data frame) which a factory-made
*_map_total_n() function took as its data argument.
Examples
# Originally reported summary data...
df <- tibble::tribble(
~x1, ~x2, ~n,
"3.43", "5.28", 90,
"2.97", "4.42", 103
)
df
#> # A tibble: 2 × 3
#> x1 x2 n
#> <chr> <chr> <dbl>
#> 1 3.43 5.28 90
#> 2 2.97 4.42 103
# ...GRIM-tested with dispersed `n` values...
out <- grim_map_total_n(df)
out
#> # A tibble: 48 × 8
#> x n n_change consistency both_consistent probability case dir
#> <chr> <int> <int> <lgl> <lgl> <dbl> <int> <fct>
#> 1 3.43 45 0 FALSE FALSE 0.55 1 forth
#> 2 5.28 45 0 FALSE FALSE 0.55 1 forth
#> 3 3.43 44 -1 TRUE TRUE 0.56 1 forth
#> 4 5.28 46 1 TRUE TRUE 0.54 1 forth
#> 5 3.43 43 -2 FALSE FALSE 0.57 1 forth
#> 6 5.28 47 2 TRUE FALSE 0.53 1 forth
#> 7 3.43 42 -3 TRUE FALSE 0.58 1 forth
#> 8 5.28 48 3 FALSE FALSE 0.52 1 forth
#> 9 3.43 41 -4 FALSE FALSE 0.59 1 forth
#> 10 5.28 49 4 FALSE FALSE 0.51 1 forth
#> # ℹ 38 more rows
# ...and faithfully reconstructed:
reverse_map_total_n(out)
#> # A tibble: 2 × 3
#> x1 x2 n
#> <chr> <chr> <dbl>
#> 1 3.43 5.28 90
#> 2 2.97 4.42 103