2 Demographics Background
library(knitr)
library(PKPDmisc)
library(tidyverse)
source("../scripts/generate_demographics.R")
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The following covariance matrix was generated from fitting the baseline demographics from a couple hundred neonates in a hospital setting, primarily the NICU.
sample_ids <- generate_demographics(500) %>%
## generate males and females
mutate(SEX = factor(rbernoulli(nrow(.)),
labels = c("FEMALE", "MALE")))
This functionality is encapsulated in the script generate_demographics.R
for use in other files.
GGally::ggpairs(sample_ids)
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
kable(head(sample_ids))
WT | CRE | AGE | PMA | HT | SEX |
---|---|---|---|---|---|
3.263 | 0.557 | 9.99 | 270 | 45.9 | FEMALE |
4.389 | 0.423 | 55.58 | 348 | 51.0 | MALE |
2.659 | 0.720 | 36.76 | 242 | 53.1 | FEMALE |
0.921 | 0.643 | 39.31 | 241 | 34.4 | FEMALE |
2.898 | 0.269 | 33.18 | 279 | 41.5 | FEMALE |
3.941 | 0.563 | 31.29 | 256 | 58.3 | MALE |
devtools::session_info()
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