Supported Methods Matrix
Current support snapshot for statistical methods, model families, and analysis capabilities in the current Licklider release.
This page is the authoritative release-facing reference for which statistical methods are currently supported in Licklider.
For the rationale behind particular defaults, see JS vs Python Execution Model.
Statistical methods
| Method | Status | Notes |
|---|---|---|
| Welch's t-test | Supported | Default for independent two-group comparisons |
| Student's t-test | Supported | Available when the analysis is intentionally configured that way |
| Mann-Whitney U | Supported | Used as a non-parametric alternative for independent groups |
| Paired t-test | Supported | Available for paired or repeated observations with two conditions |
| Wilcoxon signed-rank | Supported | Non-parametric paired alternative |
| One-way ANOVA | Supported | Standard multi-group comparison workflow |
| Kruskal-Wallis | Supported | Non-parametric multi-group alternative |
| Two-way ANOVA | Supported | Default engine policy uses Type II sum of squares |
| Repeated measures ANOVA | Supported | Available when the repeated structure is recognized and the workflow fits |
| Friedman | Supported | Non-parametric repeated-measures alternative |
| Linear regression (OLS) | Supported | For continuous outcome regression within supported assumptions |
| Logistic regression | Supported | Binary outcome modeling support is present |
| Generalized linear mixed models | Supported | Current support is focused rather than universal across every mixed-model family |
| Kaplan-Meier | Supported | Survival analysis support is part of the current public surface |
| Cox proportional hazards | Supported | Available within the current survival-analysis scope |
| Non-linear regression (4PL / Hill) | Supported | Available for supported dose-response style workflows |
| Chi-square test | Supported | Current categorical association support includes chi-square workflows |
| Fisher's exact test | Not yet supported as a first-class public surface | Do not assume parity with chi-square support yet |
| Bootstrap confidence intervals | Supported | Included as part of robustness and estimation workflows |
| Permutation tests | Supported | Available as a robustness-oriented alternative |
| Bayes factor supplement | Supported | Treated as a supplement rather than a replacement for the main frequentist result |
| Power analysis | Partial | Current public support is narrower than the full method surface |
How to read "supported"
"Supported" on this page means the current release exposes the method as part of the intended product experience.
It does not mean:
- every adjacent workflow variant is equally mature
- every edge case is automatically recognized
- every possible import shape or design flaw is handled without researcher input
Power analysis scope
Power analysis should currently be read conservatively.
- Core coverage is strongest for common t-test, ANOVA, and chi-square style use cases.
- Coverage is narrower for regression, mixed-model, and survival-analysis planning.
- If your planning question depends on a highly specialized design, do not assume first-class support without checking the surrounding docs and implementation details.
Data and workflow assumptions
Method availability depends not only on the statistical engine, but also on the recognized data shape and workflow context.
Examples:
- paired methods depend on a usable paired or subject-like structure
- repeated-measures paths depend on the data encoding repeated observations in a recognizable way
- regression support depends on a valid distinction between outcome, predictors, and design context
Related reading
- Use Figure Support Matrix for the current figure surface boundary.
- Use Active vs Legacy Implementations when a code path exists but the public support claim is unclear.