Docs
Start here when you are not yet sure which documentation section fits your question, and need to choose between onboarding, study setup, methods, quality checks, figures, reporting, or workflow guides.
When to use this page
Use /docs as the main entry point when you know your research task but do not yet know which documentation section to read first. This page helps you choose the next category based on where you are in the analysis process.
Quickest route
| If your main question is... | Go to... |
|---|---|
| I am new to Licklider and need orientation, scope, quickstart, or key terms. | Getting Started |
| I need to decide how the dataset, replicates, variables, or pre-analysis plan should be structured before analysis. | Study Setup |
| I need to choose a statistical test, model, or analysis family. | Methods |
| I need to judge assumptions, independence, missingness, diagnostics, confounding, or result validity. | Quality Checks |
| I already know the analysis goal and need to choose a figure type such as a box plot, scatter plot, Kaplan-Meier plot, or diagnostic plot. | Figures and Visualization |
| I need help writing results, disclosure text, tables, or submission-facing summaries. | Reporting and Submission |
| I want an application-oriented path organized by workflow or domain use case rather than by method. | Workflows and Applications |
Start here if you are unsure
- Start with Getting Started if you are new to the product or still clarifying product scope.
- Start with Study Setup if your main uncertainty is how to structure data or declare analysis rules before running anything.
- Start with Methods if your dataset is mostly ready and the next decision is which analysis to run.
Section guide
- Getting Started: orientation, product scope, quickstart, decision guides, and terminology.
- Study Setup: dataset structure, analysis planning, provenance, and reproducibility choices before analysis.
- Methods: choosing the statistical family that matches your research question.
- Quality Checks: checking assumptions, robustness, missingness, multiplicity, covariates, diagnostics, and validity signals.
- Figures and Visualization: matching figures to data shape and message.
- Reporting and Submission: drafting result text, disclosure language, result tables, and submission-facing outputs.
- Workflows and Applications: workflow-first and domain-oriented routes across common analysis situations.
If this is not your destination
- If you need technical reference material rather than task-based guidance, go to /reference.
Related
- Related links are registered in frontmatter and rendered below this page.