ty_simulate: Simulate a through-year system with known true growth

In throughyear: Linking, Routing and Fairness for Through-Year Assessment

Simulate a through-year system with known true growth

Description

Students grow linearly, 'theta(t) = theta0 + g * t', and take interims at 'times' (reported on their own scale, 'scale[1] + scale[2] * theta', with error from a Rasch form of 'interim_items' items) and the summative at t = 1. Late enrollers miss the first 'late_missing' interims. "Fast growers" gain an extra 'fast_extra' logits after the last interim (e.g. a spring intervention), which interims cannot reveal. They are the hardest case for prior-informed scoring.

Usage

ty_simulate(
  n_calibration = 3000,
  n_operational = 3000,
  times = c(0.2, 0.5, 0.8),
  theta0_mean = -0.6,
  theta0_sd = 1,
  growth_mean = 0.6,
  growth_sd = 0.25,
  p_fast = 0.1,
  fast_extra = 0.6,
  p_late = 0.1,
  late_missing = 2,
  scale = c(200, 10),
  interim_items = 30,
  summative_se = 0.3,
  seed = NULL
)

Arguments

n_calibration, n_operational	Cohort sizes.
times	Interim occasions as fractions of the year.
theta0_mean, theta0_sd, growth_mean, growth_sd	True-score model.
p_fast, fast_extra	Share of fast growers and their extra growth.
p_late, late_missing	Share of late enrollers and interims they miss.
scale	Interim reporting scale: intercept and slope.
interim_items	Items per interim form (sets measurement error).
summative_se	SE of the calibration cohort's summative scores.
seed	Optional seed.

Details

Two cohorts: 'calibration' (last year: summative observed, used to link) and 'operational' (this year: summative not yet taken). A second, independent set of interim scores ('*_r2') supports decision-consistency analyses.

Value

A 'ty_sim' data frame, one row per student.

Examples

sim <- ty_simulate(n_calibration = 300, n_operational = 300, seed = 1)
head(sim[c("id", "cohort", "late", "fast", "I1", "I2", "I3", "S")])

throughyear documentation built on Oct. 8, 2026, 5:07 p.m.