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randomization

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Implement proper randomization procedures for experiments. Use when: (1) Assigning participants to conditions, (2) Ensuring unbiased allocation, (3) Meeting CONSORT standards, (4) Pre-registration.

4 stars
1.2k downloads
Updated 2/2/2026

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SKILL.md

Randomization Skill

Purpose

Implement proper random assignment to minimize selection bias.

Randomization Methods

1. Simple Randomization

  • Coin flip, random number generator
  • Best for large samples (N>200)
  • Risk of imbalance in small samples

2. Block Randomization

  • Ensures equal group sizes
  • Blocks of 4, 6, or 8
  • Example: AABB, ABAB, BABA, BBAA

3. Stratified Randomization

  • Balance prognostic factors
  • Stratify by sex, age group, severity
  • Then randomize within strata

4. Minimization

  • Dynamic allocation
  • Minimizes imbalance across factors
  • Used in small trials

Implementation

Steps:

  1. Generate random sequence (with seed)
  2. Document sequence generation
  3. Implement allocation concealment
  4. Execute randomization
  5. Document actual allocation

Example (Python):

import random
random.seed(12345)  # Document seed
sequence = ['A', 'B'] * 50  # 100 participants
random.shuffle(sequence)

Version: 1.0.0

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

82/100Analyzed 2/18/2026

Well-structured skill on randomization methods for experiments. Covers 4 main methods with clear implementation steps and Python example. Located in proper skills folder. Missing tags and some CONSORT details. General research skill not tied to specific codebase.

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Metadata

Licenseunknown
Version1.0.0
Updated2/2/2026
Publisherastoreyai

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