CVrisk (version 1.2.1)

make_sample_data: Generate sample cardiovascular risk data

Description

Creates a data frame with randomly generated patient data suitable for testing cardiovascular risk calculations. The function generates realistic ranges for all standard cardiovascular risk factors.

Usage

make_sample_data(n = 100)

Value

A data frame with n rows and the following columns:

id

Sequential patient identifier (1 to n)

age

Patient age in years (30-79)

sex

Sex at birth ("female" or "male")

race

Patient race ("white", "aa", or "other")

sbp

Systolic blood pressure in mm Hg (90-200)

bp_med

Blood pressure medication status (TRUE/FALSE)

totchol

Total cholesterol in mg/dL (130-320)

hdl

HDL cholesterol in mg/dL (20-100)

lipid_med

Lipid medication status (TRUE/FALSE)

diabetes

Diabetes status (TRUE/FALSE)

smoker

Smoking status (TRUE/FALSE)

egfr

Estimated glomerular filtration rate in mL/min/1.73m2 (15-140)

bmi

Body mass index in kg/m2 (18.5-39.9)

hba1c

Hemoglobin A1c percentage (4.5-15.0 or NA)

uacr

Urine albumin-to-creatinine ratio in mg/g (0.1-25000 or NA)

zip

ZIP code (30 valid codes or NA)

Arguments

n

Number of rows to generate (default: 100)

Examples

library(CVrisk)
# Generate default 100 rows
sample_data <- make_sample_data()

# Generate 50 rows
sample_data_50 <- make_sample_data(n = 50)

# Use with compute_CVrisk
if (FALSE) {
data <- make_sample_data(n = 10)
result <- compute_CVrisk(
  data,
  scores = "ascvd_10y_accaha",
  age = "age",
  gender = "sex",
  race = "race",
  sbp = "sbp",
  totchol = "totchol",
  hdl = "hdl",
  bp_med = "bp_med",
  smoker = "smoker",
  diabetes = "diabetes"
)
}