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seanshin0214

Dr. QuantMaster MCP Server

by seanshin0214

mlm_guide

Guide to multilevel modeling with ICC calculation, random effects specification, and cross-level interaction analysis for hierarchical data structures.

Instructions

다층모형 가이드 (ICC, 랜덤효과, 교차수준 상호작용)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelsYes수준 수 (2 or 3)
random_effectsNo랜덤효과
cross_levelNo교차수준 상호작용

Implementation Reference

  • Registration of the 'mlm_guide' tool in the exported tools array, including name, description, and input schema.
    {
      name: "mlm_guide",
      description: "다층모형 가이드 (ICC, 랜덤효과, 교차수준 상호작용)",
      inputSchema: {
        type: "object",
        properties: {
          levels: { type: "number", description: "수준 수 (2 or 3)" },
          random_effects: { type: "array", items: { type: "string" }, description: "랜덤효과" },
          cross_level: { type: "boolean", description: "교차수준 상호작용" },
        },
        required: ["levels"],
      },
    },
  • Input schema for the mlm_guide tool defining parameters: levels (required), random_effects, cross_level.
    inputSchema: {
      type: "object",
      properties: {
        levels: { type: "number", description: "수준 수 (2 or 3)" },
        random_effects: { type: "array", items: { type: "string" }, description: "랜덤효과" },
        cross_level: { type: "boolean", description: "교차수준 상호작용" },
      },
      required: ["levels"],
    },
  • Handler function that executes the mlm_guide tool, providing key multilevel modeling concepts (ICC, random slopes, cross-level interactions) and example lme4 R code.
    function handleMlmGuide(args: Record<string, unknown>) {
      return {
        levels: args.levels,
        key_concepts: {
          icc: "Intraclass Correlation - 집단간 분산 비율",
          random_slope: "기울기의 집단간 변이 허용",
          cross_level: "수준간 상호작용"
        },
        r_code: "library(lme4)\nfit <- lmer(y ~ x1 + (1 + x1 | group), data = df)"
      };
    }

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