临床统计学介绍39

1、200461 为什么要做统计分析？ 统计分析的目的是应用样本样本 资料的信息,作出有 关研究总体研究总体的有效推测。 应用概要性指标概要性指标描述样本资料来实现。 这些概要性指标保留了足够的信息足够的信息 去估计研究总 体的特征。 200462 关于总体的临床研究问题关于总体的临床研究问题 在发展中国家，人工喂养相比母乳喂养能否增加母亲为HIV阳性 的婴儿生存率？ 如何建立一个心脏搭桥手术后生存率模型？病人的特征能否预测 术后生存率？相比内科治疗，搭桥手术后1，3，5年的生存率能 否改善？ 局部治疗小肝癌能否代替外科手术切除？ 根治术后应用大剂量的干扰素能否降低肝癌复发率？ 200463 今天

2、的主题 n总体，样本和个体 n资料的类型： Continuous vs. categorical n如何描述资料? 统计量 和图 n测量集中趋势和离散趋势 n标准误和95% 可信区间 n根据数据选择合适的统计方法 n诊断试验评价 200464 总体，样本和个体 “Aristotle maintained that women have fewer teeth than men; although he was twice married, it never occurred to him to verify this statement by examining his wives mouth

3、s.” - Sir Bertrand Russell, The Impact of Science on Society, 1952. “It is a capital mistake to theorize before you have data.” - Sir Arthur Conan Doyle, Scandal in Bohemia. 200465 总体，样本和个体 And, for another viewpoint: “If your experiment needs statistics, you ought to have done a better experiment.”

4、 Ernest Rutherford. The bench science perspective: you can control all the variables! Clinicians, however, know better human variation is large, and often inexplicable. Statistics help us describe it and generalize at least enough to improve our ability to practice medicine. 200466 总体，样本和个体 Aristotl

5、e 推测了一个女性总体女性总体 (比较男性总体). 他实际上手头就有一 个包含2个女人的样本个女人的样本 ，他能对这个样本中的2个个体个体进行数牙。 The population is the collection of all people about whom you would like to ask a research question. This might be a fairly clear-cut easily defined set of people: “What proportion of people 65 or older in the US today have A

6、lzheimers disease?” Or it might be a more hypothetical group: “How much of a reduction in symptomatic days could a person expect if treated with a new antiviral for flu?” 200467 总体，样本和个体 实际上，我们不可能去研究总体中的每一个对象。 所以，我们研究一个样本样本, 并将其推广到整个人群。 样本样本 量量 是样本中个体个体 的数目 (而不是对每个研究对象的测 量指标数目!) 好的研究设计能帮助我们得到一个 代表性好

7、的样本。 好的统计分析能帮助我们获得关于总体问题的答案。 200468 例子：HCC的裸鼠转移模型 免疫重建对照组 CD331.5%14.2% CD4 XX XX CD8 XX XX * 2个水平：裸鼠 细胞 200469 今天的主题 n总体，样本和个体 n资料的类型： Continuous vs. categorical n如何描述资料? 统计量 和图 n测量集中趋势和离散趋势 n标准误和95% 可信区间 n根据数据选择合适的统计方法 n诊断试验评价 2004610 数据类型 n计量资料 Quantitative: “how much ?” 连续的变量连续的变量: 年龄, 体重, 身高, 血

8、压 实际数值实际数值: 家庭的子女数, 住院天数 n分类资料 Categorical: “what type ?” 等级变量: 肿瘤分期 (I,II,III) ; 好 中 差 名义变量：男/女; 健康/生病; ABO血型 2004611 数据类型数据类型的转换 n计量数据可转换成分类数据： normal (value) vs. abnormal; “young, middle-aged, old” n将连续变量转换成等级变量减少了资料的信息量，从 而造成统计学检验的敏感度或把握度下降 2004612 今天的主题 n总体，样本和个体 n资料的类型： Continuous vs. categori

9、cal n如何描述资料? 统计量 和图 n测量集中趋势和离散趋势 n标准误和95% 可信区间 n根据数据选择合适的统计方法 n诊断试验评价 2004613 Notes: vertical axis can be count or percent in the above example, counts do not add to 74 individuals can have multiple risk factors tabular presentation may be more parsimonious for such data Risk factor for HIV 0 20 40

10、60 80 Count GayHeterIVDUOccup N = 74 分类资料的统计描述 计数 百分比 2004614 分类数据的统计描述 n构成比 n率 n比例 vs 率 n标化 2004615 下面是一组年龄数据（11例） 21, 32, 34, 34, 42, 44, 46, 48, 52, 56, 64 年龄是一个计量的变量，所以如果用条图就不合适。我 们更感兴趣的是年龄分布的一些特征： 年龄分别的中心点在哪里？如平均数 年龄的变异又是如何? 是不是有些数据跟绝大部分数据差得很多（outliers） 借助视觉工具帮助我们回答这些问题. 定量数据的统计描述定量数据的统计描述 2004

11、616 计量数据的统计描述计量数据的统计描述 图表 1. Stem and Leaf plot 2. Histogram 3. Boxplot 数字 1. Location - mean, median, mode. 2. Spread - range, variance, standard deviation，percentile 3. Shape- skewness *例外：生存资料的描述 2004617 We could group the data and tally the frequencies: But why “hide” the details? Instead, well

12、use the 10s place as stems and the units as leaves: 20: X 30: XXX 40: XXXX 50: XX 60: X 2* | 1 3* | 244 4* | 2468 5* | 26 6* | 4 Stem and Leaf Diagram stem “同一总体中的样本均数 呈正态分布” n样本均数的标准误标准误用于样本均数估计总体的均数。 标准误是一个重要的统计量，用于计算样本均数的可信度，取 决于标准差和样本量。但实际上两者并不独立，当样本量增加 时，标准差往往减少。 2004627 正态分布 ( basis of statist

13、ical inference for many populations ) Mean = median = mode. all = same value in the distribution remember: 68.3% of data is between - 1.00 s.d. and + 1.00 s.d. 95.0% “ “ “ “ “ “ “ - 1.96 s.d. and + 1.96 s.d. 95.5% “ “ “ “ “ “ “ - 2.00 s.d. and + 2.00 s.d. 99.7% “ “ “ “ “ “ “ - 3.00 s.d. and + 3.00 s

14、.d. 2004628 今天的主题 n总体，样本和个体 n资料的类型： Continuous vs. categorical n如何描述资料? 统计量 和图 n测量集中趋势和离散趋势 n标准误和95% 可信区间 n根据数据选择合适的统计方法 n诊断试验评价 2004629 推断性统计推断性统计 推广结论: 样本总体 评价证据的强度 比较 预测 2004630 计量资料的统计方法 正态分布非正态分布 配对资料（配对资料（2组组) 配对t检验符号检验 符号等级检验 成组比较成组比较 (2组）组）成组比较t检验Wilcoxon Mann case series ; review of medical

15、 literature n2. 组织一个假设假设 ( asking the right question ) ; good hypotheses are: Specific, Measurable, and Plausible n3. 检验假设检验假设 ( assumptions vs. type of data ) n4. 再验证验证 always Question the VALIDITY of the result(s) : Chance ; Bias ; and Causality 2004640 结论的准确性 nChance : role of random error in out

16、come measure(s) ( p - value ; power of the study and the confidence interval ) - largely determined by sample size nBias : role of systematic error in outcome measure(s) nSelection bias - subjects not representativ nInformation bias - error(s) in subject data / classification nConfounding - 3rd vari

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