Define the time metricMake the data structure visible.
Use a common model sampleRecord checks and uncertainty.
Model individual changeConnect output to interpretation.

WHAT IS INSIDE

A reproducible path through the workflow.

01

Audit repeated observations

Check person-time keys, observed waves, missing outcomes, and the model sample.

02

Estimate baseline clustering

Use the unconditional means model to describe between-person variation.

03

Fit linear growth

Estimate average change and heterogeneity in intercepts and slopes.

04

Explain conditional change

Add mentoring and person-level predictors, compare models, and report trajectories with uncertainty.

SCOPE AND BOUNDARIES

Match the workflow
to the question.

Before adapting the example:

  • Define the unit, repeated-measure schedule, and time origin.
  • Run the complete synthetic example.
  • Use only a de-identified working copy of real data.
  • Review model or transformation assumptions with the committee.

The number and timing of observations must support the chosen functional form, covariance, and random-effects structure.

OUTPUT-ONLY PUBLIC PREVIEW

Explore the complete worked example.

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Growth Modeling Basics · Dissertation Stats Helper

The preview shows results, figures, and guidance. The paid version includes all editable source and reusable code. Source code and session information are omitted.

YOUR DIGITAL DOWNLOAD

Run the example.
Make it your own.

  • Complete editable R Markdown source
  • Synthetic data and reproducible generator
  • Worked HTML report and reusable exports
  • Dynamic reporting and diagnostic guidance
  • Setup, generation, version, and license documentation

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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