EDUCATION PREMIUM WORKFLOW · VERSION 1.0

Evaluate the program.
Respect the design.

A modular R Markdown workflow for four distinct education evaluation designs: propensity-score weighting and matching, difference-in-differences, regression discontinuity, and interrupted time series—with design-specific assumptions and diagnostics.

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One-time purchase · Individual-use license · Secure digital delivery

Start with assignmentDefine the intervention, comparison group, timing, assignment mechanism, and estimand.

Check design assumptionsEstimate propensity-score weights and matching; review overlap, balance, and weight behavior.

Report sensitivityFit difference-in-differences and event-study models with school-clustered uncertainty.

WHAT IS INSIDE

A complete education-analysis workflow.

The package connects design-specific data audits, model choice, diagnostics, interpretation, and reporting in one reproducible analysis.

Define the intervention, comparison group, timing, assignment mechanism, and estimand

Define the intervention, comparison group, timing, assignment mechanism, and estimand.

Estimate propensity-score weights and matching; review overlap, balance, and weight behavior

Estimate propensity-score weights and matching; review overlap, balance, and weight behavior.

Fit difference-in-differences and event-study models with school-clustered uncertainty

Fit difference-in-differences and event-study models with school-clustered uncertainty.

Fit local linear regression-discontinuity models and examine bandwidth sensitivity

Fit local linear regression-discontinuity models and examine bandwidth sensitivity.

Fit interrupted time-series models with autocorrelation-aware uncertainty

Fit interrupted time-series models with autocorrelation-aware uncertainty.

Generate design-specific interpretation, limitations, and a reporting checklist

Generate design-specific interpretation, limitations, and a reporting checklist.

DESIGNED FOR EDUCATION RESEARCH

Causal program evaluation.

This workflow is useful when:

You evaluate a school, district, or education program without randomized assignment.
Your study has a plausible comparison group, threshold, panel, or repeated time series.
You need to connect assumptions to a specific causal estimand.
Your committee expects diagnostics and sensitivity analyses tailored to the design.

These examples do not make observational data randomized; causal conclusions depend on the assignment mechanism, assumptions, measurement, and design-specific evidence.

PUBLIC PREVIEW

Review the rendered analysis.

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Quasi-Experimental Program Evaluation · Public Preview

The public preview shows output, figures, and interpretation without exposing source code or session information. The paid version includes the complete editable R Markdown source and all analysis code.

THE DOWNLOADABLE PACKAGE

Run the example.
Then adapt your study.

The release uses a documented synthetic education dataset. Run the complete example first, then adapt the clearly marked settings and models to your research design.

Editable R Markdown source and rendered report
Four synthetic education evaluation examples
Propensity-score weighting, matching, and balance outputs
Difference-in-differences and event-study outputs
Regression-discontinuity bandwidth sensitivity
Interrupted time-series estimates and plots
Start guide, reporting checklist, and individual-use license

The workflow supports analysis and documentation. The researcher remains responsible for selecting methods that fit the study and for reviewing conclusions with the dissertation advisor, committee, or a qualified statistician.

VERSION 1.0.0

Complete workflow.
$59 one time.

Pay securely and receive the version 1.0.0 ZIP with the editable analysis, synthetic data, documentation, and rendered report.

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