This function arranges and annotates a data frame based on specified types of treatment effect estimates (RR or RD). It supports a variety of sorting options including alphabetical, magnitude (ascending or descending), E-value bound (ascending or descending), custom order, and a default alias for backward compatibility. It also handles original scale estimates when available.
This function arranges and annotates a data frame based on specified types of treatment effect estimates (RR or RD). It supports a variety of sorting options including alphabetical, magnitude (ascending or descending), E-value bound (ascending or descending), custom order, and a default alias for backward compatibility. It also handles original scale estimates when available.
Usage
group_tab(
df,
type = c("RD", "RR"),
order = c("alphabetical", "magnitude_desc", "magnitude_asc", "evaluebound_desc",
"evaluebound_asc", "custom", "default"),
custom_order = NULL
)
group_tab(
df,
type = c("RD", "RR"),
order = c("alphabetical", "magnitude_desc", "magnitude_asc", "evaluebound_desc",
"evaluebound_asc", "custom", "default"),
custom_order = NULL
)Arguments
- df
Data frame containing the variables of interest, or a list containing the results data frame and label mapping from transform_to_original_scale().
- type
Type of treatment effect to analyze. One of 'RR' (Risk Ratio) or 'RD' (Risk Difference). Defaults to 'RD'.
- order
Sorting option for outcomes. Options are:
'alphabetical': sort by outcome name (A–Z)
'magnitude_desc': sort by absolute effect size, descending (default for 'magnitude')
'magnitude_asc': sort by absolute effect size, ascending
'evaluebound_desc': sort by E-value bound, descending
'evaluebound_asc': sort by E-value bound, ascending
'custom': user-defined order (requires custom_order)
'default': alias for 'magnitude_desc' (deprecated)
Default is 'default'.
- custom_order
Character vector specifying a custom outcome ordering, used when order = 'custom'. Must contain all outcomes exactly once.
Value
A data frame arranged according to `order`, annotated with:
Estimate category (positive, negative, not reliable)
Formatted label for the effect and confidence interval
Optional original-scale label if _original columns are present
A data frame arranged according to `order`, annotated with:
Estimate category (positive, negative, not reliable)
Formatted label for the effect and confidence interval
Optional original-scale label if _original columns are present
Details
The function detects whether `df` is a list output from transform_to_original_scale() and extracts `results_df` and `label_mapping` accordingly. It then ensures an `outcome` column, applies any label mapping, and sorts based on the chosen `order`. New options 'magnitude_desc' and 'magnitude_asc' sort by absolute effect size; 'evaluebound_desc' and 'evaluebound_asc' sort by the E-Value bound; 'alphabetical' sorts by outcome name; 'custom' respects a user-provided vector; 'default' is an alias for 'magnitude_desc'.
The function detects whether `df` is a list output from transform_to_original_scale() and extracts `results_df` and `label_mapping` accordingly. It then ensures an `outcome` column, applies any label mapping, and sorts based on the chosen `order`. New options 'magnitude_desc' and 'magnitude_asc' sort by absolute effect size; 'evaluebound_desc' and 'evaluebound_asc' sort by the E-Value bound; 'alphabetical' sorts by outcome name; 'custom' respects a user-provided vector; 'default' is an alias for 'magnitude_desc'.
Examples
# descending magnitude (default for 'default')
result_df <- group_tab(df = analysis_df, order = 'default')
#> Error in group_tab(df = analysis_df, order = "default"): could not find function "group_tab"
# ascending magnitude
result_df <- group_tab(df = analysis_df, order = 'magnitude_asc')
#> Error in group_tab(df = analysis_df, order = "magnitude_asc"): could not find function "group_tab"
# strongest E-value bound first
result_df <- group_tab(df = analysis_df, order = 'evaluebound_desc')
#> Error in group_tab(df = analysis_df, order = "evaluebound_desc"): could not find function "group_tab"
# alphabetical
result_df <- group_tab(df = analysis_df, order = 'alphabetical')
#> Error in group_tab(df = analysis_df, order = "alphabetical"): could not find function "group_tab"
# custom ordering
custom_order <- c('Outcome3','Outcome1','Outcome2')
result_df <- group_tab(df = analysis_df, order = 'custom', custom_order = custom_order)
#> Error in group_tab(df = analysis_df, order = "custom", custom_order = custom_order): could not find function "group_tab"
# descending magnitude (default for 'default')
result_df <- group_tab(df = analysis_df, order = 'default')
#> Error in group_tab(df = analysis_df, order = "default"): could not find function "group_tab"
# ascending magnitude
result_df <- group_tab(df = analysis_df, order = 'magnitude_asc')
#> Error in group_tab(df = analysis_df, order = "magnitude_asc"): could not find function "group_tab"
# strongest E-value bound first
result_df <- group_tab(df = analysis_df, order = 'evaluebound_desc')
#> Error in group_tab(df = analysis_df, order = "evaluebound_desc"): could not find function "group_tab"
# alphabetical
result_df <- group_tab(df = analysis_df, order = 'alphabetical')
#> Error in group_tab(df = analysis_df, order = "alphabetical"): could not find function "group_tab"
# custom ordering
custom_order <- c('Outcome3','Outcome1','Outcome2')
result_df <- group_tab(df = analysis_df, order = 'custom', custom_order = custom_order)
#> Error in group_tab(df = analysis_df, order = "custom", custom_order = custom_order): could not find function "group_tab"