- name
- openclaw-r-stats
- metadata
- openclaw
- emoji
- 📊
- requires
- bins
- description
- >
- ZH
- 统计分析, 回归, 检验, 预测, 显著性, 生存分析, 元分析, 贝叶斯;
- JA
- 統計分析, 回帰, 検定, 予測; KO: 통계분석, 회귀, 검정;
- ES
- análisis estadístico, regresión; FR: analyse statistique, régression;
- DE
- statistische Analyse, Regression; PT: análise estatística, regressão;
- RU
- статистический анализ, регрессия; AR: تحليل إحصائي.
OpenClaw R Stats
When to Use
User asks for any statistical analysis, hypothesis testing, group comparison, prediction, association, survival analysis, meta-analysis, causal inference, power/sample size, or mentions R statistical packages.
What This Skill Does NOT Do
- Claim causality from observational data (use "associated with")
- Run large exploratory fishing without clear user intent
- Silently ignore assumption violations
- Report only p-values (always include effect sizes and CIs)
Pre-Flight (Mandatory)
- Confirm dataset exists and is readable
- Run schema inspection:
bash {baseDir}/scripts/run-rstats.sh schema --data <path> - Report: rows, columns, types, missing values
- If missing > 5%, warn. If n < 30, warn small sample.
Environment Setup
First time or errors: bash {baseDir}/scripts/run-rstats.sh doctor
Install by profile (only when needed):
| Profile | Script | Methods |
|---|---|---|
| Core | install-core.R | t-test, regression, ANOVA, chi-sq |
| Survival | install-survival.R | KM, Cox, competing risks, RMST |
| Missing | install-missing.R | MICE, MCAR test |
| Mixed | install-mixed.R | LMM, GLMM, GEE, ICC |
| Bayes | install-bayes.R | brms, Bayes factors |
| Causal | install-causal.R | PSM, IPTW, IV, DiD, RDD, TMLE |
| Meta | install-meta.R | meta-analysis, NMA |
| SEM | install-sem.R | SEM, CFA, lavaan |
| Diagnostic | install-diagnostic.R | ROC, kappa, alpha |
| Advanced | install-advanced.R | GAM, quantile, zero-inflated |
| Power | install-power.R | power/sample size |
Workflow
- Determine analysis type (see references/METHOD_TABLE.md)
- Inspect dataset schema
- Build JSON spec:
{
"dataset_path": "<path>",
"analysis_type": "<type>",
"outcome": "<column>",
"predictors": ["<col1>"],
"hypothesis": "<plain language>",
"alpha": 0.05,
"seed": 42,
"output_dir": "<path>"
}- Save as .json, run:
bash {baseDir}/scripts/run-rstats.sh analyze --spec <path> - Read summary.json + report.md
- Present: Summary → Statistics → Interpretation → Plots → Assumptions → Caveats
Analysis Selection
For the complete 82-method table with user intent mapping, see references/METHOD_TABLE.md.
Quick lookup — most common:
| Intent | analysis_type |
|---|---|
| Compare 2 groups | ttest or wilcoxon |
| Compare 3+ groups | anova or kruskal |
| Categorical association | chisq or fisher |
| Predict continuous | linear_regression |
| Predict binary | logistic_regression |
| Survival curves | kaplan_meier |
| Survival regression | cox_regression |
| Meta-analysis | meta_analysis |
| Causal effect | propensity_match or did |
| Power/sample size | power_analysis |
Automatic Method Switching
- Non-normal + n < 30 →
wilcoxonoverttest - Unequal variance → Welch t-test (
equal_var: false) - Expected cells < 5 →
fisheroverchisq - Overdispersion in Poisson → suggest negative binomial
- Heteroscedastic residuals → robust SE warning
Reporting Rules (Non-Negotiable)
Every analysis MUST include:
- Sample size (n) and missing data handling
- Method name and rationale
- Point estimates with confidence intervals
- Effect sizes (Cohen's d, η², R², OR, HR, etc.)
- Assumption check results
- Limitations
Language: "associated with" / "evidence suggests" — NEVER "proves" / "causes"
Spec Field Reference
See references/SPEC_REFERENCE.md for required/optional fields per analysis_type.