Simulating to create the bradley data

Creating the bradley data set, working from the top part of Table 1 of Bradley SM et al. (2019) “Incidence, Risk Factors, and Outcomes Associated With In-Hospital Acute Myocardial Infarction” JAMA Network Open 2(1): e187348. https://doi.org/10.1001/jamanetworkopen.2018.7348

Code

library(tidyverse)

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.4.0     ✔ purrr   1.0.1
✔ tibble  3.1.8     ✔ dplyr   1.1.0
✔ tidyr   1.3.0     ✔ stringr 1.5.0
✔ readr   2.1.3     ✔ forcats 1.0.0
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

1 Simulating Cases

Code

set.seed(20200114)
status <- rep("Case", 687)
age0 <- round(rnorm(687, mean = 73.3, sd = 10.1))
sex0 <- c(rep("Male", 677), rep("Female", 10))
race_eth0 <- c(rep("white", 546), rep("non-white", 141))
married0 <- c(rep(1, 356), rep(0, 331))
location0 <- c(rep("ICU", 186), rep("Bed", 446), 
               rep("Other", 55))

dat_cases <- tibble(
    status, age = sample(age0), sex = sample(sex0),
    race_eth = sample(race_eth0), married = sample(married0),
    location = sample(location0)
)

2 Simulating Controls

Code

status <- rep("Control", 687)
age0 <- round(rnorm(687, mean = 73.4, sd = 10.3))
sex0 <- c(rep("Male", 666), rep("Female", 21))
race_eth0 <- c(rep("white", 527), rep("non-white", 160))
married0 <- c(rep(1, 310), rep(0, 377))
location0 <- c(rep("ICU", 65), rep("Bed", 580), 
               rep("Other", 42))

dat_controls <- tibble(
    status, age = sample(age0), sex = sample(sex0), 
    race_eth = sample(race_eth0), married = sample(married0), 
    location = sample(location0)
)

3 Combining the Data

Code

bradley_raw <- bind_rows(dat_cases, dat_controls)
bradley_raw$subject <- sample(1:nrow(bradley_raw))

bradley <- bradley_raw %>%
    select(subject, everything()) %>%
    arrange(subject)

bradley

# A tibble: 1,374 × 7
   subject status    age sex   race_eth married location
     <int> <chr>   <dbl> <chr> <chr>      <dbl> <chr>   
 1       1 Control    64 Male  white          1 Bed     
 2       2 Case       70 Male  white          1 ICU     
 3       3 Control    68 Male  white          0 Bed     
 4       4 Control    76 Male  white          1 Bed     
 5       5 Control    70 Male  white          1 Bed     
 6       6 Case       89 Male  white          1 Other   
 7       7 Control    75 Male  white          0 Bed     
 8       8 Control    84 Male  white          1 Bed     
 9       9 Control    80 Male  white          1 ICU     
10      10 Control    89 Male  white          0 Bed     
# … with 1,364 more rows

Code

write_csv(bradley, "data/bradley.csv")