The tests a table carries and prints under itself: a crosstab's chi-squared or ANOVA, a
regression's model-fit statistics and global tests. get_test() hands them back as a tidy
tibble — one row per test, keyed by var (the row variable, the predictor, or ""
for the whole table) and col (the column variable it keys under) — so a test can be
filtered, reshaped or reported like any other data. A new kind of test is new rows, never new
columns.
The remaining columns name the statistic (test, statistic, df1, df2,
pvalue), the base it was computed on (n, min_e, deff) and its effect
size (effect_size, es_type). Per-CELL contributions to the chi-squared are not here:
they are the ctr field of the cells themselves (tabs$Total$ctr).
Value
A tibble of tests — empty, with the same columns, when the table ran none (build them
with tab(test = TRUE)); NULL only when x has lost its attributes.
See also
tab() for test =, tab_structure() and tab_columns() for the rest of a table's
metadata.
Examples
tabs <- tab(forcats::gss_cat, race, marital, test = TRUE)
get_test(tabs)
#> # A tibble: 1 × 14
#> var col test statistic df1 df2 pvalue n min_e effect_size
#> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 race marital chi2 997. 10 NA 7.44e-208 21483 1.55 0.152
#> # ℹ 4 more variables: es_type <chr>, pvalue_exact <dbl>, deff <dbl>,
#> # outcome <chr>