httk (version 1.8)

httkpop_generate: Generate a virtual population

Description

Generate a virtual population

Usage

httkpop_generate(method, 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"))

Arguments

method

The population-generation method to use. Either "virtual individuals" or "direct resampling." Short names may be used: "d" or "dr" for "direct resampling", and "v" or "vi" for "virtual individuals".

nsamp

The desired number of individuals in the virtual population. nsamp need not be provided if gendernum is provided.

gendernum

Optional: A named list giving the numbers of male and female individuals to include in the population, e.g. list(Male=100, Female=100). Default is NULL, meaning both males and females are included, in their proportions in the NHANES data. If both nsamp and gendernum are provided, they must agree (i.e., nsamp must be the sum of gendernum).

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 only a single value is provided, both minimum and maximum ages will be set to that value; e.g. agelim_years=3 is equivalent to agelim_years=c(3,3). If agelim_years is provided and agelim_months is not, agelim_years will override the default value of agelim_months.

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 agelim_years. If only a single value is provided, both minimum and maximum ages will be set to that value; e.g. agelim_months=36 is equivalent to agelim_months=c(36,36). If agelim_months is provided and agelim_years is not, agelim_months will override the default values of agelim_years.

weight_category

Optional: The weight categories to include in the population. Default is c('Underweight', 'Normal', 'Overweight', 'Obese'). User-supplied vector must contain one or more of these strings.

gfr_category

The kidney function categories to include in the population. Default is c('Normal','Kidney Disease', 'Kidney Failure') to include all kidney function levels.

reths

Optional: a character vector giving the races/ethnicities to include in the population. Default is c('Mexican American','Other Hispanic','Non-Hispanic White','Non-Hispanic Black','Other'), to include all races and ethnicities in their proportions in the NHANES data. User-supplied vector must contain one or more of these strings.

Value

A data.table where each row represents an individual, and each column represents a demographic, anthropometric, or physiological parameter.

References

Ring, Caroline L., et al. "Identifying populations sensitive to environmental chemicals by simulating toxicokinetic variability." Environment International 106 (2017): 105-118.

Examples

# NOT RUN {
 
# }
# NOT RUN {
#Simply generate a virtual population of 100 individuals,
 #using the direct-resampling method
 set.seed(42)
httkpop_generate(method='direct resampling', nsamp=100)
#Generate a population using the virtual-individuals method,
#including 80 females and 20 males,
#including only ages 20-65,
#including only Mexican American and 
 #Non-Hispanic Black individuals,
 #including only non-obese individuals
httkpop_generate(method = 'virtual individuals',
gendernum=list(Female=80, 
Male=20),
agelim_years=c(20,65), 
reths=c('Mexican American', 
'Non-Hispanic Black'),
weight_category=c('Underweight',
'Normal',
'Overweight'))
# }