cov_forest_data: Produce dataset for covariate forest plotting

In NMproject: Script Based 'NONMEM' Model Development

Produce dataset for covariate forest plotting

Description

The main workhorse for computing uncertainty quantiles of covariate effects in different subpopulations.

Usage

cov_forest_data(m, covariate_scenarios)

Arguments

m	An nm object.
covariate_scenarios	A data.frame. Need columns cov, value and (optional) text. See details for more information.

Details

The column cov in covariate_scenarios refers to covariate variables in the dataset. The column value refers to covariate values of importance. Typically these will be quantiles of continuous variables and categories (for categorical covariates). The column text is option but is a labelling column for cov_forest_plot() to adjust how the covariate scenarios are printed on the axis

Value

dplyr::tibble with quantile information suitable for cov_forest_plot().

Examples

## requires NONMEM to be installed
## Not run: 

dcov <- input_data(m1, filter = TRUE)
dcov <- dcov[!duplicated(dcov$ID), ]

covariate_scenarios <- dplyr::bind_rows(
  dplyr::tibble(cov = "HEALTHGP", value = c(0, 1)),
  dplyr::tibble(cov = "HEPATIC", value = unique(dcov$HEPATIC[dcov$HEPATIC > -99])),
  dplyr::tibble(cov = "BWTIMP", value = c(50, 80, 120)),
  dplyr::tibble(cov = "ECOG", value = c(0, 1, 2, 3)),
  dplyr::tibble(cov = "BEGFRIMP", value = quantile(dcov$BEGFR[dcov$BEGFR > -99])),
  dplyr::tibble(cov = "RACE", value = c(1, 2), text = c("white", "black")),
  dplyr::tibble(cov = "PPI", value = c(0, 1)),
  dplyr::tibble(cov = "H2RA", value = c(0, 1))
)

dplot <- cov_forest_data(m1, covariate_scenarios = covariate_scenarios)
cov_forest_plot(dplot)

## End(Not run)

NMproject documentation built on Sept. 30, 2022, 1:06 a.m.