Vignette: Creating an Age Pyramid with ClinicoPathDescriptives • ClinicoPath

# Create a sample data frame
set.seed(123) # for reproducibility
cohort_data <- data.frame(
  patient_id = 1:150,
  age = sample(20:85, 150, replace = TRUE),
  gender = sample(c("F", "M"), 150, replace = TRUE, prob = c(0.6, 0.4))
)

# View the first few rows
head(cohort_data)
#>   patient_id age gender
#> 1          1  50      M
#> 2          2  70      F
#> 3          3  33      F
#> 4          4  61      F
#> 5          5  69      F
#> 6          6  62      F

# This code simulates how the jamovi module would be called in an R environment.
# You would need the ClinicoPathDescriptives package installed.

# Load the library
library(ClinicoPathDescriptives)
#> Registered S3 method overwritten by 'future':
#>   method               from      
#>   all.equal.connection parallelly
#> Warning: replacing previous import 'dplyr::select' by 'jmvcore::select' when
#> loading 'ClinicoPathDescriptives'

# Run the age pyramid analysis
results <- agepyramid(
    data = cohort_data,
    age = "age",
    gender = "gender",
    female = "F", # Specify that 'F' represents females
    bin_width = 10, # Use 10-year age bins
    plot_title = "Age Distribution of Study Cohort"
)

# To view the results:
# View the summary table
print(results$pyramidTable)
#> 
#>  Population Data                  
#>  ──────────────────────────────── 
#>    Population    Female    Male   
#>  ──────────────────────────────── 
#>    (80,85]            4       1   
#>    (70,80]           13      10   
#>    (60,70]           13       8   
#>    (50,60]           17      11   
#>    (40,50]           21      10   
#>    (30,40]           12       5   
#>    (20,30]           14       9   
#>    (10,20]            2       0   
#>  ────────────────────────────────

# View the plot
print(results$plot)