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rw-statistics-audit

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Original

English
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Translation

Chinese

RW Statistics Audit

RW Statistics Audit

审查研究中的分析单位、重复层级、统计方法和结果报告是否对得上，不把报告审查当成重新分析。
Verify whether the analysis units, replication levels, statistical methods, and result reports in the research are consistent, and do not treat report review as re-analysis.

启动

Initiation

  1. 读取 
    references/standalone.md
    、
    references/method.md
    和 
    references/standards.md
    。
  2. 读取用户本轮提供的材料；没有材料时，只完成当前证据允许的部分。
  3. 需要规则判断时检索 
    references/atoms.jsonl
    ；遇到相似任务时读取 
    references/cases.md
    。
  4. 需要选择方法或工具时读取 
    references/domain-guide.md
    ，并使用 
    assets/worksheet.md
    组织交付。
  5. 读取 
    references/acceptance.md
    。
    references/behavior-tests.json
    只用于测试，不作为用户任务事实。
  6. 当前文献、API、报告规范和期刊要求可能变化时，打开 
    references/source-map.md
    中的官方链接核验并记录日期。
  1. Read 
    references/standalone.md
    , 
    references/method.md
    and 
    references/standards.md
    .
  2. Read the materials provided by the user in this session; if no materials are available, only complete the parts permitted by the current evidence.
  3. Retrieve 
    references/atoms.jsonl
    when rule-based judgments are needed; read 
    references/cases.md
    when encountering similar tasks.
  4. Read 
    references/domain-guide.md
    when selecting methods or tools, and use 
    assets/worksheet.md
    to organize deliverables.
  5. Read 
    references/acceptance.md
    . 
    references/behavior-tests.json
    is only used for testing and not as factual information for user tasks.
  6. When current literature, APIs, reporting specifications and journal requirements may change, open the official links in 
    references/source-map.md
    to verify and record the date.

工作阶段

Work Phases

  1. 固定文稿、表格、图和分析说明的版本，列出主要判断、结局和分析对象。
  2. 识别观察单位、独立分析单位、聚类结构、技术重复、生物重复和实际样本量。
  3. 逐项提取统计方法、模型、变量、比较、时间点、协变量、缺失数据处理和多重比较处理。
  4. 核对方法选择与设计、数据类型、分布、配对、重复测量和独立性是否一致。
  5. 检查效应估计、不确定区间、样本量、精确 p 值、单位、分母和缺失数是否报告并前后一致。
  6. 把正文、表格、图注和补充材料中的每个统计判断连接到对应分析和数据层级。
  7. 把问题分为错误、信息不足、需统计人员复核和报告通过；没有数据时不声称完成重算。
  1. Fix the versions of manuscripts, tables, figures and analysis descriptions, and list key judgments, outcomes and analysis objects.
  2. Identify observational units, independent analysis units, clustering structures, technical replicates, biological replicates and actual sample sizes.
  3. Extract statistical methods, models, variables, comparisons, time points, covariates, missing data handling and multiple comparison handling item by item.
  4. Verify whether method selection is consistent with study design, data type, distribution, pairing, repeated measures and independence.
  5. Check whether effect estimates, uncertainty intervals, sample sizes, exact p-values, units, denominators and missing counts are reported and consistent across all sections.
  6. Connect each statistical judgment in the main text, tables, figure captions and supplementary materials to the corresponding analysis and data levels.
  7. Classify issues into errors, insufficient information, requiring statistical personnel review, and report approval; do not claim completion of recalculation when no data is available.

运行规则

Operating Rules

  • 观察单位、独立分析单位和图中数据点不是同一个概念，必须分别写清。
  • 技术重复不能自动增加独立样本量，生物重复也要按设计判断独立性。
  • 统计方法名称不能替代模型设定、比较对象、协变量和处理规则。
  • p 值不能单独说明效应大小、方向、精度或实际意义。
  • 无统计学显著性不能改写成没有效应，显著也不能改写成重要或因果。
  • 主要与次要结局、预设与探索分析、单次与重复分析要分开。
  • 多重比较、缺失数据、模型假设和异常值处理要说明是否预设和怎样执行。
  • 样本量要给出每组分母、排除和缺失，不能只给总 n。
  • 图中的误差条要说明统计量、计算层级和样本数。
  • 百分比必须能回到分子和分母，四舍五入不能造成表间冲突。
  • 正文、表格、图注和补充材料的数字冲突进入阻断状态，不自动选择一个。
  • 报告规范用于检查信息是否齐全，不证明模型正确、假设成立或结果可重复。
  • 没有原始数据、分析代码或充分汇总量时，只做报告审查，不生成重算结果。
  • 临床、监管或高风险结论需要领域统计人员复核，Skill 不替代签字。
  • Observational units, independent analysis units and data points in figures are not the same concept and must be clearly described separately.
  • Technical replicates cannot automatically increase independent sample size; biological replicates also need to be judged for independence according to the study design.
  • Statistical method names cannot replace model settings, comparison objects, covariates and processing rules.
  • p-values cannot alone explain effect size, direction, precision or practical significance.
  • Lack of statistical significance cannot be rephrased as no effect; significance cannot be rephrased as importance or causality.
  • Primary vs. secondary outcomes, prespecified vs. exploratory analyses, and single vs. repeated analyses must be separated.
  • Handling of multiple comparisons, missing data, model assumptions and outliers must state whether they were prespecified and how they were implemented.
  • Sample sizes must provide denominators, exclusions and missing counts for each group, not just the total n.
  • Error bars in figures must specify the statistic, calculation level and sample size.
  • Percentages must be traceable back to numerators and denominators; rounding must not cause conflicts between tables.
  • Numerical conflicts between the main text, tables, figure captions and supplementary materials trigger a blocking state, and no option is automatically selected.
  • Reporting specifications are used to check whether information is complete, not to prove model correctness, assumption validity or result reproducibility.
  • Only conduct report review and do not generate recalculation results when there is no raw data, analysis code or sufficient aggregated data.
  • Clinical, regulatory or high-risk conclusions require review by domain statisticians; Skill does not substitute for signature.

输出

Output

  • 分析单位、重复层级、结局和方法对应表。
  • 数字、模型、假设和报告缺口清单。
  • 错误、信息不足、需复核、通过和失效状态。
  • Corresponding table of analysis units, replication levels, outcomes and methods.
  • List of gaps in numbers, models, assumptions and reports.
  • Statuses of errors, insufficient information, requiring review, approval and invalidation.

停止条件

Stop Conditions

  • 分析单位或重复层级不清时，不给统计报告通过状态。
  • 关键数字在正文、图表或补充材料中冲突时停止最终结论。
  • 没有数据和分析代码时，不声称复现或重新分析。
  • 不根据 p 值替作者判断临床、政策或实际意义。
  • Do not grant the "approved" status to the statistical report when analysis units or replication levels are unclear.
  • Stop drawing final conclusions when key numbers conflict in the main text, charts or supplementary materials.
  • Do not claim reproduction or re-analysis when no data or analysis code is available.
  • Do not judge clinical, policy or practical significance on behalf of authors based on p-values.

独立运行

Independent Operation

  • 默认不读取私人工作区、个人语料目录或预设 research-lab。
  • 用户提供的文件、文本、链接和数据是当前任务输入，不是安装依赖。
  • 网络不可用时，使用 Skill 内的稳定方法继续；需要当前事实的部分标记为待核验。
  • 本包内其他科研 Skill 存在时可以接续；单独安装时直接返回下一步说明，不停止当前任务。
  • By default, do not read private workspaces, personal corpus directories or preset research-lab.
  • Files, text, links and data provided by the user are inputs for the current task, not installation dependencies.
  • When the network is unavailable, continue using stable methods within the Skill; mark parts requiring current facts as pending verification.
  • Can connect with other research Skills in this package if they exist; when installed separately, directly return instructions for the next step without stopping the current task.

来源纪律

Source Discipline

  • 把用户材料、公开来源、当前推断和未知事项分开。
  • 报告规范只检查报告透明度，不自动证明设计质量。
  • 公开来源摘要保存在 Skill 内；需要版本、费用、政策、API 或期刊现状时回到官方页面。
  • 不生成不存在的论文、数据、DOI、工具运行结果或期刊要求。
  • Separate user materials, public sources, current inferences and unknown matters.
  • Reporting specifications only check report transparency, and do not automatically prove study design quality.
  • Summaries of public sources are stored within the Skill; return to official pages when information about versions, fees, policies, APIs or current journal requirements is needed.
  • Do not generate non-existent papers, data, DOIs, tool operation results or journal requirements.