add_disproportionality: Add disproportionality estimates to data frame with expected...

In pvda: Disproportionality Functions for Pharmacovigilance

Add disproportionality estimates to data frame with expected counts

Description

Add disproportionality estimates to data frame with expected counts

Usage

add_disproportionality(
  df = NULL,
  df_syms = NULL,
  da_estimators = c("ic", "prr", "ror"),
  rule_of_N = 3,
  conf_lvl = 0.95
)

Arguments

df	Intended use is on the output tibble from add_expected_counts.
df_syms	A list built from df_colnames through conversion to symbols.
da_estimators	Character vector specifying which disproportionality estimators to use, in case you don't need all implemented options. Defaults to c("ic", "prr", "ror").
rule_of_N	Numeric value. Sets estimates for ROR and PRR to NA when observed counts are strictly less than the passed value of rule_of_N. Default value is 3, 5 is sometimes used as a more liberal alternative. Set to NULL if you don't want to apply any such rule.
conf_lvl	Confidence level of confidence or credibility intervals. Default is 0.95 (i.e. 95 % confidence interval).

Value

The passed data frame with disproportionality point and interval estimates.

pvda documentation built on May 29, 2024, 3 a.m.