httkpop_direct_resample {httk} | R Documentation |
Generate a virtual population by directly resampling the NHANES data.
Description
Generate a virtual population by directly resampling the NHANES data.
Usage
httkpop_direct_resample(
nsamp = NULL,
gendernum = NULL,
agelim_years = NULL,
agelim_months = NULL,
weight_category = c("Underweight", "Normal", "Overweight", "Obese"),
gfr_category = c("Normal", "Kidney Disease", "Kidney Failure"),
reths = c("Mexican American", "Other Hispanic", "Non-Hispanic White",
"Non-Hispanic Black", "Other"),
gfr_resid_var = TRUE,
ckd_epi_race_coeff = FALSE,
nhanes_mec_svy
)
Arguments
nsamp |
The desired number of individuals in the virtual population.
|
gendernum |
Optional: A named list giving the numbers of male and
female individuals to include in the population, e.g. |
agelim_years |
Optional: A two-element numeric vector giving the
minimum and maximum ages (in years) to include in the population. Default is
c(0,79). If |
agelim_months |
Optional: A two-element numeric vector giving the
minimum and maximum ages (in months) to include in the population. Default
is c(0, 959), equivalent to the default |
weight_category |
Optional: The weight categories to include in the
population. Default is |
gfr_category |
The kidney function categories to include in the
population. Default is |
reths |
Optional: a character vector giving the races/ethnicities to
include in the population. Default is |
gfr_resid_var |
Logical value indicating whether or not to include residual variability when generating GFR values. (Default is TRUE.) |
ckd_epi_race_coeff |
Logical value indicating whether or not to use the "race coefficient" from the CKD-EPI equation when estimating GFR values. (Default is FALSE.) |
nhanes_mec_svy |
|
Value
A data.table where each row represents an individual, and each column represents a demographic, anthropometric, or physiological parameter.
Author(s)
Caroline Ring
References
Ring CL, Pearce RG, Setzer RW, Wetmore BA, Wambaugh JF (2017). “Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability.” Environment International, 106, 105–118.