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Compute interaction disproportionality

Source: R/compute_interaction.R
compute_interaction.Rd

[Experimental] Returns the information component of interaction for a set of 3 variables, usually 2 drugs and an adr.

Usage

compute_interaction(
  .data,
  y,
  x,
  z,
  alpha = 0.05,
  na_format = "-",
  dig = 2,
  export_raw_values = FALSE,
  min_n_obs = 0
)

Arguments

.data

The data.table to compute from.

y

A character vector, one or more variable to explain.

x

A character vector, one or more explaining variable.

z

A character vector, one or more explaining variable.

alpha

Alpha risk.

na_format

Character string to fill NA values in ror and ci legends.

dig

Number of digits for rounding (this argument is passed to cff)

export_raw_values

A logical. Should the raw values be exported?

min_n_obs

A numeric, compute disproportionality only for pairs with at least min_n_obs cases.

Value

A data.table, with Information Component (IC) of interaction, and its credibility interval (at 1 - alpha). Significance as signif_ic, if export_raw_values is TRUE).

A data.table with columns

  • y, x and z, same as input

  • n_obs the number of observed cases

  • n_exp the number of expected cases

  • ic the Information Component

  • ic_tail the tail probability of the IC

  • ci_level the confidence interval level

  • Additional columns, if export_raw_values is TRUE:

  • a, b, c, d the counts in the contingency table

  • signif_ic the significance of the Information Component

  • Additional columns, if export_raw_values is TRUE:

  • n_* the counts of each setting

  • signif_ic the significance of the Information Component

Details

Significance is similar to usual disproportionality (see compute_dispro()).

See also

compute_dispro(), compute_or_mod(), add_drug(), add_adr()

Examples

# Interaction on reporting of colitis with ipilimumab and nivolumab
demo <-
  demo_ |>
  add_drug(
    d_code = ex_$d_drecno,
    drug_data = drug_
  ) |>
  add_adr(
    a_code = ex_$a_llt,
    adr_data = adr_
  )
#> ℹ `.data` detected as `demo` table.
#> ℹ `.data` detected as `demo` table.

demo |>
  compute_interaction(
    y = "a_colitis",
    x = "nivolumab",
    z = "ipilimumab"
  )
#> # A tibble: 1 × 8
#>   y         x         z          n_obs n_exp    ic ic_tail ci_level
#>   <chr>     <chr>     <chr>      <dbl> <dbl> <dbl>   <dbl> <chr>   
#> 1 a_colitis nivolumab ipilimumab    18  7.88  1.14   0.400 95%