Capability-Ecological Developmental Model (CEDM) Analysis

Implements the Capability-Ecological Developmental Model (CEDM) for longitudinal and multilevel data. The package supports estimation and interpretation of models examining how socioeconomic status (SES), health indicators, and contextual factors jointly relate to academic outcomes. Functionality includes: (1) classification of ecological capability regimes (amplifying, neutral, compensatory); (2) estimation of moderated multilevel models with higher-order interaction terms; (3) causal mediation analysis using doubly robust estimation; (4) random-effects within-between (REWB) decomposition; (5) nonlinear moderation using restricted cubic splines; (6) clustering of longitudinal health trajectories; and (7) sensitivity analysis using the impact threshold for a confounding variable (ITCV) and robustness-to-replacement (RIR) measures. The package is designed for use with general longitudinal multilevel datasets.

CEDMr

Overview

CEDMr implements the Capability-Ecological Developmental Model (CEDM) (Hait, 2025), a theoretical framework for studying how socioeconomic status (SES), health indicators (e.g., BMI), and ecological contexts jointly shape academic achievement across childhood.

The package operationalizes all five CEDM theoretical propositions into directly callable R functions and is designed to work with any longitudinal multi-level dataset, including ECLS-K:2011 and similar national surveys.

The Five CEDM Propositions

Installation

# Install from GitHub
# install.packages("remotes")
remotes::install_github("causalfragility-lab/CEDMr")

Quick Start

Simulate CEDM data

library(CEDMr)

# Simulate 3000 observations across three ecological regimes
sim <- cedm_simulate(n = 3000, n_waves = 5, seed = 42)
table(sim$regime)
#>
#>   amplifying compensatory      neutral
#>         1000         1000         1000

Classify ecological capability regimes

sim <- classify_regime(sim, ses_var = "SES", ses_tertiles = TRUE)
table(sim$cedm_regime)

Fit the CEDM production function

# Base model: SES × health interaction
base_model <- cedm_production(
  data        = sim,
  outcome_var = "achievement",
  ses_var     = "SES",
  health_var  = "health",
  model       = "base",
  center      = TRUE
)
print(base_model)

# Full regime model: SES × health × regime (three-way interaction)
regime_model <- cedm_production(
  data        = sim,
  outcome_var = "achievement",
  ses_var     = "SES",
  health_var  = "health",
  regime_var  = "cedm_regime",
  model       = "regime",
  center      = TRUE
)
print(regime_model)

Causal mediation analysis (Proposition 4)

med <- cedm_mediation(
  data        = sim,
  outcome_var = "achievement",
  ses_var     = "SES",
  health_var  = "health",
  n_boot      = 500,
  seed        = 42
)
print(med)

Within-between decomposition (Proposition 3)

rewb <- cedm_rewb(
  data        = sim,
  outcome_var = "achievement",
  health_var  = "health",
  id_var      = "id",
  time_var    = "wave",
  ses_var     = "SES"
)
print(rewb)

Health trajectory clustering (Proposition 3)

traj <- cedm_trajectory(
  data        = sim,
  health_var  = "health",
  id_var      = "id",
  time_var    = "wave",
  k           = 3,
  outcome_var = "achievement",
  ses_var     = "SES"
)
print(traj)
traj$plot

Sensitivity analysis (Proposition 5)

sens <- cedm_sensitivity(base_model, term = "SES")
print(sens)

Run the full pipeline in one call

pipeline <- cedm_full_pipeline(
  data        = sim,
  outcome_var = "achievement",
  ses_var     = "SES",
  health_var  = "health",
  id_var      = "id",
  time_var    = "wave",
  n_boot      = 200,
  seed        = 42
)
print(pipeline)
pipeline$plots$regimes
pipeline$plots$interaction

Function Reference

Citation

If you use CEDMr in your research, please cite:

Hait, S. (2026). Socioeconomic Status, Health, and Academic Achievement:
A Capability-Ecological Developmental Model. Manuscript under review.

Hait, S. (2026). CEDMr: Capability-Ecological Developmental Model (CEDM)
Analysis Toolkit. R package version 0.1.0.
https://github.com/causalfragility-lab/CEDMr

License

MIT © 2026 Subir Hait