Prepare and audit the data
Import data, review missingness and distributions, verify observed ranges, define variables, and document the analysis sample.
PREMIUM R MARKDOWN WORKFLOW · VERSION 1.0
Understand the process.
Report it clearly.
A complete, editable workflow for mediation, moderation, and conditional process analysis—with bootstrap inference, interaction probing, diagnostics, and results text designed for dissertation research.
One-time purchase · Individual-use license · Secure digital delivery
Run before adaptingStart with a complete example that reproduces from beginning to end.
Probe the interactionMove beyond a coefficient to simple slopes and Johnson–Neyman results.
Write from resultsGenerate narrative from the fitted models instead of fixed example numbers.
WHAT IS INSIDE
A complete conditional-process workflow.
The package separates the questions answered by mediation, moderation, and moderated mediation, then connects each estimate to diagnostics and reporting decisions.
Estimate simple mediation
Fit the component models and bootstrap the indirect, direct, and total associations.
Test and explain moderation
Use HC3 robust inference, conditional predictions, an interaction plot, and simple slopes.
Find regions of significance
Calculate and plot Johnson–Neyman boundaries inside the observed moderator range.
Estimate moderated mediation
Bootstrap conditional indirect effects and the index of moderated mediation at meaningful support values.
Diagnose and report
Review residuals, heteroskedasticity, influence, covariate sensitivity, dynamic narrative, and a reporting checklist.
DESIGNED FOR DOCTORAL RESEARCH
Use it when your theory describes a process, a boundary condition, or both.
This workflow is useful when:
- You have continuous predictor, mediator, moderator, and outcome variables.
- You need bootstrap inference for an indirect effect.
- You need to probe and visualize an interaction transparently.
- You need conditional indirect effects and an index of moderated mediation.
- You need a reproducible analysis trail for committee review.
Binary, ordinal, count, multilevel, latent-variable, and longitudinal models require extensions beyond this introductory regression-based workflow.
PUBLIC PREVIEW
Review the analysis output before purchasing.
The public preview shows the rendered analysis and guidance. The purchased package contains the editable R Markdown code, runnable data, and reusable exports.
THE DOWNLOADABLE PACKAGE
Built to run,
learn from, and adapt.
The download is a versioned ZIP package. Run the synthetic example first, then change the clearly marked settings, formulas, variables, and covariates for your study.
- Editable R Markdown source file
- Complete rendered HTML report
- Reproducible synthetic psychology dataset
- Package installation helper and RStudio project
- Bootstrap mediation and conditional-process code
- Modern interaction and conditional-effect figures
- Dynamic results-writing template
- Reusable CSV result tables
- Start guide, reporting checklist, and individual license
Purchase includes the files and documented workflow. Study-specific consulting, model selection, data review, and interpretation support are available separately.
INTRODUCTORY RELEASE
Complete workflow.
$59 one time.
Pay securely and receive immediate access to the version 1.0 download. Existing purchasers can retrieve the current product files through their order account.
Checkout is being connected. Please email hello@dissertationstatshelper.com if you would like to be notified as soon as purchasing opens.
COMMON QUESTIONS
Before you
purchase.
Do I need experience with R?
Basic familiarity with RStudio helps. The package includes an installation helper, a runnable synthetic example, clearly marked settings, and explanations for each analysis stage.
Can I use the workflow with my own data?
Yes. Run the synthetic example first, then update the file path, variable names, coding, covariates, and formulas. You remain responsible for ensuring the model fits your design and measures.
Does this prove causal mediation?
No. The workflow repeatedly distinguishes statistical indirect effects from causal mechanisms. Causal claims require a design, temporal ordering, assumptions, and measurement quality that support them.
Can I share the files with classmates or a lab?
The $59 product includes an individual-use license. You may share your rendered research results with your committee or coauthors, but the editable source files may not be redistributed.
Is consulting included?
No. The purchase includes the documented workflow and files. Project-specific statistical consultation can be arranged separately through Dissertation Stats Helper.