summary_functions {cards}

Summary Functions

Description

• continuous_summary_fns() returns a named list of summary functions for continuous variables. Some functions include slight modifications to their base equivalents. For example, the min() and max() functions return NA instead of Inf when an empty vector is passed. Statistics "p25" and "p75" are calculated with quantile(type = 2), which matches SAS's default value.

• categorical_summary_fns() returns a named list of summary statistics for categorical variables. Options are "n", "N", and "p". If a user requests, for example, only "p", the function will return "n" and "N" as well, since they are needed to calculate "p". These statistics will be stored as a vector within the tabulation list element.

• missing_summary_fns() returns a named list of summary functions suitable for variable-level summaries, such as number and rate of missing data.

Usage

continuous_summary_fns(
  summaries = c("N", "mean", "sd", "median", "p25", "p75", "min", "max"),
  other_stats = NULL
)

categorical_summary_fns(summaries = c("n", "p", "N"), other_stats = NULL)

missing_summary_fns(
  summaries = c("N_obs", "N_miss", "N_nonmiss", "p_miss", "p_nonmiss")
)

Arguments

summaries

(character)
a character vector of results to include in output.

• continuous_summary_fns(): Select one or more from 'N', 'mean', 'sd', 'median', 'p25', 'p75', 'min', 'max'.

• categorical_summary_fns(): Select one or more from 'n', 'p', 'N'.

• missing_summary_fns(): Select one or more from 'N_obs', 'N_miss', 'N_nonmiss', 'p_miss', 'p_nonmiss'.

other_stats

(named list)
named list of other statistic functions to supplement the pre-programmed functions.

Value

continuous_summary_fns() and missing_summary_fns() return a named list of summary functions, categorical_summary_fns() returns a named list of summary statistics.

Examples

# continuous variable summaries
ard_continuous(
  ADSL,
  variables = "AGE",
  statistic = ~ continuous_summary_fns(c("N", "median"))
)

# categorical variable summaries
ard_categorical(
  ADSL,
  variables = "AGEGR1",
  statistic = ~ categorical_summary_fns(c("n", "N"))
)

# summary for rates of missing data
ard_missing(
  ADSL,
  variables = c("AGE", "AGEGR1"),
  statistic = ~ missing_summary_fns()
)