Tidying methods for a spicy_continuous_table

Standard broom::tidy() and broom::glance() interfaces for an object returned by table_continuous(). They re-shape the underlying long-format data into the two canonical broom views so the descriptive table can be consumed by any downstream tidyverse-stats pipeline.

Usage

# S3 method for class 'spicy_continuous_table'
tidy(x, ...)

# S3 method for class 'spicy_continuous_table'
glance(x, ...)

Arguments

x

A spicy_continuous_table returned by table_continuous().

...

Currently ignored. Present for compatibility with the broom::tidy() / broom::glance() generics.

Value

A tbl_df.

Details

tidy() returns one row per (variable x group) (or per variable when by is not used) with broom-conventional columns: variable (the column name), label (the label the rows display for it, see labels), group (NA without by), .group_role (the role of group: "group", or "missing" for the group of missing by values; NA without by), estimate (the empirical mean), std.error (sd / sqrt(n)), conf.low, conf.high (the mean confidence interval at ci_level), n, weighted_n (the sum of the weights, NA without weights), median, q1, q3, min, max, sd: the columns of tidy.spicy_continuous_svy_table(), the design ones (df, deff) aside.

glance() returns one row per variable with the omnibus group comparison (when by is used), the requested effect size and the balance diagnostic. Columns: variable, label, test_type, statistic, df, df.residual, p.value, es_type, es_value, es_ci_lower, es_ci_upper, smd_type, smd_value, nobs (the rows described, a row of zero weight left out), weighted_nobs (the sum of their weights, NA without weights). Without by, only variable, label, nobs and weighted_nobs are populated; the other columns are NA. The schema is fixed: smd_type / smd_value are present whether or not smd = TRUE, like every other comparison column here, and are NA when the table carries no standardized mean difference, as in glance.spicy_categorical_table(). Index this frame by NAME rather than by position.

See also

as.data.frame.spicy_continuous_table() for the displayed table as a data frame, and output = "long" of table_continuous() for the long format; tidy.spicy_continuous_lm_table() for the model-based companion.