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Add quantiles for a subject-level covariate

Source: R/nif_ntile.R
add_ntile.Rd

Calculate quantiles for a column's values across all subjects. Each subject gets the same n-tile value across all their rows. The input column must have exactly one distinct value per subject (e.g., age, weight, baseline values).

Usage

add_ntile(nif, input_col, n = 4, ntile_name = NULL)

Arguments

nif

A nif object

input_col

The column name to calculate n-tiles for (must have one distinct entry per subject)

n

The number of quantiles (n-tiles) to generate (default = 4)

ntile_name

Custom name for the output column. If NULL, uses x_NTILE format where x is the name of the input column

Value

A nif object with a new column containing the n-tile values (1 to n), named either x_NTILE (default) or the custom name specified in ntile_name

See also

dplyr::ntile() for the underlying n-tile calculation

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)

examplinib_sad_nif |>
  add_ntile("WEIGHT") |>
  plot(dose_norm = TRUE, facet = "WEIGHT_NTILE")


examplinib_poc_nif |>
  add_ntile("WEIGHT", n = 5) |>
  distinct(ID, WEIGHT, WEIGHT_NTILE) |>
  ggplot(aes(x = WEIGHT_NTILE, y = WEIGHT)) +
  geom_point() +
  labs(title = "Plasma concentrations by WEIGHT quartiles") +
  theme_bw()