mcp-statistical-analysis
CommunityMaster advanced MCP stats for clinical insights.
Data & Analytics#statistical-analysis#power-analysis#survival-analysis#clinical-research#propensity-score#roc-analysis
Authoru9401066
Version1.0.0
Installs0
System Documentation
What problem does it solve?
The MCP-based statistical toolkit enables researchers to perform advanced analyses (survival analysis, propensity scoring, ROC analysis, and power calculations) on clinical datasets with reproducible workflows.
Core Features & Use Cases
- Survival analysis with Kaplan-Meier curves, log-rank tests, and Cox proportional hazards regression for treatment effect estimation.
- Propensity score methods including estimation, matching, IPTW/ATE/ATT, and covariate balance assessment for observational studies.
- ROC/AUC analysis with calibration checks and comparison across models for diagnostic performance.
- Power and sample size calculations to inform study design and feasibility.
Quick Start
Preview your dataset and initiate a survival, propensity, ROC, or power analysis path to generate actionable results.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: mcp-statistical-analysis Download link: https://github.com/u9401066/automl-stat-mcp/archive/main.zip#mcp-statistical-analysis Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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