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enrollcast enrollcast website

Project Status: Active – The project has reached a stable, usable state and is being actively developed. name status badge R-CMD-check Codecov test coverage

enrollcast projects school enrollment using the cohort survival / grade progression ratio method, implemented as a matrix projection. It works at any level of aggregation (school, district, LEA, city-wide) and any number of grades, because it operates on a single grade-by-year enrollment series.

Awesome hex logo provided by Adam Higerd.

Installation

install.packages("enrollcast")

Install the development version from GitHub:

# install.packages("pak")
pak::pak("localopen/enrollcast")

Usage

library(enrollcast)

# Historical grade-level enrollment (long format).
history <- data.frame(
  year = rep(2021:2023, each = 3),
  grade = factor(rep(c("K", "1", "2"), 3), levels = c("K", "1", "2")),
  enrollment = c(100, 90, 80, 110, 95, 88, 120, 99, 91)
)

# 1. Calculate progression ratios.
ratios <- progression_ratios(history, method = "mean")
ratios
#>   grade_from grade_to     ratio
#> 1          K        1 0.9250000
#> 2          1        2 0.9678363

# 2. Project forward. The entry grade (K) is supplied exogenously.
base <- history[history$year == 2023, c("grade", "enrollment")]
projection <- project_enrollment(
  base = base,
  ratios = ratios,
  horizon = 3,
  entry = c(125, 130, 128),
  start_year = 2023
)
projection
#>   year grade enrollment
#> 1 2024     K  125.00000
#> 2 2024     1  111.00000
#> 3 2024     2   95.81579
#> 4 2025     K  130.00000
#> 5 2025     1  115.62500
#> 6 2025     2  107.42982
#> 7 2026     K  128.00000
#> 8 2026     1  120.25000
#> 9 2026     2  111.90607

Inspect the underlying projection matrix at any time:

progression_matrix(ratios)
#>       K         1 2
#> K 0.000 0.0000000 0
#> 1 0.925 0.0000000 0
#> 2 0.000 0.9678363 0

Multiple aggregation units

enrollcast projects one series per call. To project many schools or LEAs, split and map:

# fmt: skip
school_history <- data.frame(
  school = rep(c("North", "South"), each = 9),
  year = rep(2021:2023, each = 3, times = 2),
  grade = factor(rep(c("K", "1", "2"), times = 6), levels = c("K", "1", "2")),
  enrollment = c(100, 90, 80, 110, 95, 88, 120, 99, 91, 120, 
                 110, 100, 130, 115, 108, 140, 119, 111)
)

projections <- lapply(
  split(school_history, school_history$school),
  function(df) {
    ratios <- progression_ratios(df)
    base <- df[df$year == max(df$year), c("year", "grade", "enrollment")]
    project_enrollment(base, ratios, horizon = 3, entry = rep(100, 3))
  }
)

projections$North
#>   year grade enrollment
#> 1 2024     K  100.00000
#> 2 2024     1  111.00000
#> 3 2024     2   95.81579
#> 4 2025     K  100.00000
#> 5 2025     1   92.50000
#> 6 2025     2  107.42982
#> 7 2026     K  100.00000
#> 8 2026     1   92.50000
#> 9 2026     2   89.52485

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.