Compares multiple outcomes against an intervention in a summary table

The outcome table is a simple summary of a binary or categorical outcome in a data set compared by intervention groups. The comparison is independent of any covariates, and is a preliminary output prior to more formal statistical analysis or model fitting.

Usage

compare_outcomes(
  df,
  ...,
  label_fn = label_extractor(df),
  units = extract_units(df),
  override_type = list(),
  layout = "compact",
  override_percent_dp = list(),
  override_real_dp = list(),
  p_format = names(.pvalue.defaults),
  font_size = getOption("tableone.font_size", 8),
  font = getOption("tableone.font", "Arial"),
  footer_text = NULL,
  show_binary_value = NULL,
  raw_output = FALSE
)

Arguments

df: a dataframe of individual observations. If using the tidyselect syntax data grouping defines the intervention group and should be present. if the formula interface is used the first variable in the right hand side of the formula is used as the intervention, in which case grouping is ignored.
...: the outcomes are specified either as a tidyselect specification, in which case the grouping of the df input determines the intervention and the output is the same as a compare_population() call with a tidyselect. Alternatively a set of formulae can be provided that specify the outcomes on the left hand side, e.g. outcome1 ~ intervention + cov1, outcome2 ~ intervention + cov1, ... in this case the intervention must be the same for all formulae and used to determine the comparison groups.
label_fn: (optional) a function for mapping a co-variate column name to printable label. This is by default a no-operation and the output table will contain the dataframe column names as labels. A simple alternative would be some form of dplyr::case_when lookup, or a string function such as stringr::str_to_sentence. (N.b. this function must be vectorised). Any value provided here will be overridden by the options("tableone.labeller" = my_label_fn) which allows global setting of the labeller.
units: (optional) a named list of units, following a c(<colname_1> = "<unit_1>", <colname_2> = "<unit_2>", ...) format. columns not present in this list are assumed to have no units. Units may be involved in the formatting of the summary output.
override_type: (optional) a named list of data summary types. The default type for a column in a data set are calculated using heurisitics depending on the nature of the data (categorical or continuous), and result of normality tests. if you want to override this the options are "subtype_count","median_iqr","mean_sd","skipped" and you specify this on a column by column bases with a named list (e.g c("Petal.Width"="mean_sd")). Overriding the default does not check the type of data is correct for the summary type and will potentially cause errors if this is not done correctly.
layout: (optional) various layouts are defined as default. As of this version of tableone they are "relaxed","compact","micro","simple","single","missing". The layouts can be customised using the options options("tableone.format_list"=list(...)"), and this is described in more detail in the vignettes.
override_percent_dp: (optional) a named list of overrides for the default precision of formatting percentages, following a c(<colname_1> = 2, <colname_2> = 4, ...) format. columns not present in this list will use the defaults defined in the layout. See the vignette on customisation.
override_real_dp: (optional) a named list of overrides for the default precision of formatting real values, following a c(<colname_1> = 2, <colname_2> = 4, ...) format. columns not present in this list will use the defaults defined in the layout. See the utils::vignette("customisation", package="tableone").
p_format: the format of the p-values: one of "sampl", "nejm", "jama", "lancet", "aim" but any value here is overridden by the option("tableone.pvalue_formatter"=function(...))
font_size: (optional) the font size for the table in points
font: (optional) the font family for the table (which will be matched to closest on your system)
footer_text: any text that needs to be added at the end of the table, setting this to FALSE dsables the whole footer (as does options("tableone.hide_footer"=TRUE)).
show_binary_value: if set this will filter the display of covariates where the number of possibilities is exactly 2 to this value.
raw_output: return comparison as t1_signif dataframe rather than formatted table

Value

a huxtable formatted table.

Details

It reports summary counts for the outcomes and a measure of significance of the relationship between outcome and intervention. Interpretation of significance tests, should include Bonferroni adjustment.