calc_sample_size
Calculate required sample sizes for statistical tests including t-tests, ANOVA, regression, and proportion analysis to ensure adequate study power.
Instructions
필요 표본크기 계산 (t-test, ANOVA, regression, proportion)
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| test_type | Yes | 검정 유형 | |
| effect_size | Yes | 효과크기 (Cohen's d, f, f²) | |
| alpha | No | 유의수준 (기본: 0.05) | |
| power | No | 검정력 (기본: 0.80) | |
| groups | No | 집단 수 (ANOVA) | |
| predictors | No | 예측변수 수 (회귀) |
Implementation Reference
- src/tools/index.ts:1144-1191 (handler)The handler function executing the core logic for calc_sample_size tool. Computes required sample size for various tests (t-test, ANOVA, regression, etc.) using approximate formulas based on effect size, alpha, and power.
function handleCalcSampleSize(args: Record<string, unknown>) { const testType = args.test_type as string; const effectSize = args.effect_size as number; const alpha = (args.alpha as number) || 0.05; const power = (args.power as number) || 0.80; // Simplified sample size formulas const zAlpha = alpha === 0.05 ? 1.96 : (alpha === 0.01 ? 2.576 : 1.645); const zBeta = power === 0.80 ? 0.84 : (power === 0.90 ? 1.28 : 0.52); let n: number; let formula: string; switch (testType) { case "t_test_two": n = Math.ceil(2 * ((zAlpha + zBeta) / effectSize) ** 2); formula = "n per group = 2 × ((z_α + z_β) / d)²"; break; case "t_test_paired": n = Math.ceil(((zAlpha + zBeta) / effectSize) ** 2); formula = "n = ((z_α + z_β) / d)²"; break; case "anova": const groups = (args.groups as number) || 3; n = Math.ceil((groups * (zAlpha + zBeta) ** 2) / (effectSize ** 2)); formula = "n per group = k × (z_α + z_β)² / f²"; break; case "regression": const predictors = (args.predictors as number) || 5; n = Math.ceil((8 / (effectSize ** 2)) + predictors); formula = "n ≈ 8/f² + k (Green, 1991 rule)"; break; default: n = Math.ceil(2 * ((zAlpha + zBeta) / effectSize) ** 2); formula = "Generic formula used"; } return { test_type: testType, effect_size: effectSize, alpha, power, required_n: n, formula, interpretation: `${power * 100}% 검정력으로 효과크기 ${effectSize} 탐지에 필요한 최소 표본: ${n}`, note: "실제 계산은 G*Power 또는 pwr 패키지 사용 권장" }; } - src/tools/index.ts:108-126 (registration)Tool registration entry in the exported tools array, defining the name, description, and input schema for validation.
name: "calc_sample_size", description: "필요 표본크기 계산 (t-test, ANOVA, regression, proportion)", inputSchema: { type: "object", properties: { test_type: { type: "string", enum: ["t_test_two", "t_test_paired", "anova", "regression", "proportion", "chi_square"], description: "검정 유형" }, effect_size: { type: "number", description: "효과크기 (Cohen's d, f, f²)" }, alpha: { type: "number", description: "유의수준 (기본: 0.05)" }, power: { type: "number", description: "검정력 (기본: 0.80)" }, groups: { type: "number", description: "집단 수 (ANOVA)" }, predictors: { type: "number", description: "예측변수 수 (회귀)" }, }, required: ["test_type", "effect_size"], }, }, - src/tools/index.ts:795-796 (registration)Registration in the handleToolCall switch statement, dispatching calls to the specific handler function.
return handleCalcSampleSize(args); case "calc_power": - src/tools/index.ts:110-125 (schema)Input schema definition for the calc_sample_size tool, specifying parameters like test_type, effect_size, alpha, power with types, enums, and required fields.
inputSchema: { type: "object", properties: { test_type: { type: "string", enum: ["t_test_two", "t_test_paired", "anova", "regression", "proportion", "chi_square"], description: "검정 유형" }, effect_size: { type: "number", description: "효과크기 (Cohen's d, f, f²)" }, alpha: { type: "number", description: "유의수준 (기본: 0.05)" }, power: { type: "number", description: "검정력 (기본: 0.80)" }, groups: { type: "number", description: "집단 수 (ANOVA)" }, predictors: { type: "number", description: "예측변수 수 (회귀)" }, }, required: ["test_type", "effect_size"], },