Audit category coding, reference levels, missingness, and sparse outcome cells
Audit category coding, reference levels, missingness, and sparse outcome cells.
EDUCATION PREMIUM WORKFLOW · VERSION 1.0
Choose the right outcome model.
Explain the result.
A complete workflow for binary, ordered, and unordered educational outcomes, including coding audits, logistic models, proportional-odds checks, adjusted probabilities, calibration, discrimination, and school-clustered uncertainty.
One-time purchase · Individual-use license · Secure digital delivery
Match model to outcomeAudit category coding, reference levels, missingness, and sparse outcome cells.
Report probabilitiesFit binary logistic models and translate coefficients into adjusted probabilities.
Check model fitFit proportional-odds models and examine the proportional-odds assumption.
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.
Fit binary logistic models and translate coefficients into adjusted probabilities
Fit binary logistic models and translate coefficients into adjusted probabilities.
Fit proportional-odds models and examine the proportional-odds assumption
Fit proportional-odds models and examine the proportional-odds assumption.
Fit multinomial models for unordered outcomes and compare predicted probabilities
Fit multinomial models for unordered outcomes and compare predicted probabilities.
Review discrimination, calibration, influence, and school-clustered uncertainty
Review discrimination, calibration, influence, and school-clustered uncertainty.
Generate dynamic interpretation and guidance on when GEE or multilevel models are needed
Generate dynamic interpretation and guidance on when GEE or multilevel models are needed.
DESIGNED FOR EDUCATION RESEARCH
Binary, ordinal, and multinomial outcomes.
This workflow is useful when:
- Your outcome is binary, ordered categorical, or nominal with multiple categories.
- You need predictions or probabilities rather than odds ratios alone.
- Your outcomes are clustered within schools or other educational settings.
- You need to document model assumptions and compare plausible approaches.
Complex survey designs, very sparse categories, time-to-event outcomes, latent transitions, and multi-level generalized models require additional methods.
PUBLIC PREVIEW
Review the rendered analysis.
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
- Synthetic educational outcome data
- Binary, ordinal, and multinomial model examples
- Adjusted probability tables and accessible figures
- Calibration, discrimination, and assumption checks
- Dynamic reporting text and model comparison
- 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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