compareGroups包——快速生成统计汇总三线表—科研工具箱

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compareGroups 包

方便的统计汇总

图片[1]-compareGroups包——快速生成统计汇总三线表—科研工具箱-叨客学习资料网
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示例数据:

PREDIMED研究,针对高心血管风险患者饮食脂质的多中心研究,the PREDIMED study
数据预处理

data(predimed)
# 将生存数据整合放入
predimed$tmain <- with(predimed, Surv(toevent, event == \"Yes\"))
attr(predimed$tmain, \"label\") <- \"AMI, stroke, or CV Death\"

将所有要分析的数据放进数据框,尽量不要有无用数据

流程

1. 计算统计描述:compareGroups

1.1 Usage:

compareGroups(formula, data, subset, na.action = NULL, y = NULL, Xext = NULL, 
  selec = NA, method = 1, timemax = NA, alpha = 0.05, min.dis = 5, max.ylev = 5, 
  max.xlev = 10, include.label = TRUE, Q1 = 0.25, Q3 = 0.75, simplify = TRUE, 
  ref = 1, ref.no = NA, fact.ratio = 1, ref.y = 1, p.corrected = TRUE, 
  compute.ratio = TRUE, include.miss = FALSE, oddsratio.method = \"midp\", 
  chisq.test.perm = FALSE, byrow = FALSE, chisq.test.B = 2000, chisq.test.seed = NULL, 
  Date.format = \"d-mon-Y\", var.equal = TRUE, conf.level = 0.95, surv=FALSE)

1.2 重要参数说明:

  1. formula: .表示全部,-删去变量,例如:group ~ . - toevent - event,公式可为空,或不含分组,则统计整体的统计描述
  2. subset: subset = sex == \"Female\"对整个data起作用
  3. selec:selec = list(hormo = sex == \"Female\", waist = waist > 20)对某个变量起作用的筛选
    • 公式中可以出现多次重复变量,对应可有多个变量筛选,例如:
      compareGroups(group ~ age + sex + bmi + bmi + waist + hormo, data = predimed, selec = list(bmi.1 = !is.na(hormo)))
      bmi.1对应第二次出现的bmi
  4. method:
    默认所有的连续变量为正态分布,用ANOVA检验,可以定义具体变量,method=c(waist = 2)改变其分布,取值说明如下

     

    • 1:正态分布,ANOVA或t-test,多组间两两比较用Tukey
    • 2:非正态,Kruskal,BH校正
    • 3:分类,卡方或Fisher
    • NA:Shapiro-Wilks test 检测是否是正态分布,此外配合两个参数:

       

      • alpha:决定Shapiro-Wilks检验的p值界值
      • min.dis:当水平数少于此界值,转化为分类变量
    • 注:当自变量为Surv对象时,用logrank检验
  5. max.ylev, max.xlev:分别规定分组变量与自变量水平数的最大值,
  6. include.label:如果数据框设置有变量label时,TRUE打印label,否则打印name
  7. Q1,Q3:当非正态分布时,设定显示的分位值,默认上下四分位数
  8. simplify:默认TRUE,删除空的因子水平,为FALSE时无法计算P值
  9. ref, ref.no:当分组变量为二分类时,可以计算OR,为time-to-event的Surv时,可以计算HR,均为单因素分析
    • ref定义参照分类水平,用1,2,3,…表示,默认为1,也可定义部分变量,如ref=c(smoke=2)
    • ref.no:定义自变量中因子水平相同的水平为参照水平,不区分大小写,在所有分类变量中找同名水平
    • ref.y:计算OR时,分组变量的参照水平,默认为1
  10. fact.ratio:对于连续变量,定义增加单位,例如fact.ratio=c(bmi=2),表示bmi每增加2的OR
  11. timemax:当自变量有Surv对象时,统计描述为中位随访时间的发生率,timemax设定描述的随访时间点,timemax=c(tmain=3)
  12. include.miss: 默认FALSE,TRUE时将缺失值归为”Missing”水平进行统计描述

1.3 compareGroups对象的summary

返回一个列表包含每个自变量显示详细的统计量:包括p.trend,p.overall,两两比较的P值

>res <- compareGroups(group ~ age + sex + smoke + waist + hormo, 
                     method = c(waist = 2), data = predimed)
>summary(res[c(2)])

row-variable: Sex 

               Male Female Male (row%) Female (row%) p.overall p.trend  p.Control vs MedDiet + Nuts p.Control vs MedDiet + VOO
[ALL]          2679 3645   42.36243    57.63757                                                                               
Control        812  1230   39.76494    60.23506      8.1e-05   0.388386 0.000133                    0.358324                  
MedDiet + Nuts 968  1132   46.09524    53.90476                                                                               
MedDiet + VOO  899  1283   41.20073    58.79927                                                                               
               p.MedDiet + Nuts vs MedDiet + VOO
[ALL]                                           
Control        0.002076                         
MedDiet + Nuts                                  
MedDiet + VOO                              

1.4 compareGroups对象的plot

对具体变量可以绘图
Usage:

plot(x, file, type = \"pdf\", bivar = FALSE, z=1.5, 
  n.breaks = \"Sturges\", perc = FALSE, ...)

bivar显示分组统计图,当分组变量为Surv时,分类变量为KM曲线,连续变量为标注结局的变量-时间散点图

1.5 compareGroups对象的update

usage:

res <- update(object=res, ...)

参数同compareGroups

1.6 compareGroups对象的getResults

Usage:

getResults(obj, what = \"descr\")

what可选: “descr”, “p.overall”, “p.trend”, “p.mul” and “ratio”,获取对应统计量

2. 创建统计表:createTable

2.1 Usage:

createTable(x, hide = NA, digits = NA, type = NA, show.p.overall = TRUE,
           show.all, show.p.trend, show.p.mul = FALSE, show.n, show.ratio =
           FALSE, show.descr = TRUE, show.ci = FALSE, hide.no = NA, digits.ratio = NA,
           show.p.ratio = show.ratio, digits.p = 3, sd.type = 1, q.type = c(1, 1),
           extra.labels = NA)

该功能创建两个三线表,一个是统计汇总表,一个是统计方法概要表,

2.2 重要参数

  1. hide, hide.no:结果隐藏的变量,同ref,ref.no的变量设定,其中hide与ref不同的地方在于,hide可以以变量水平设定参考变量,而ref只能以水平索引,例如update(restab, hide = c(sex = \"Male\"))
  2. digits,digits.ratio: 统计描述的小数点,可以设定具体变量的小数点位数,例如digits=c(age=2),digits.ratio显示OR或HR的小数点位数
  3. type: 分类变量的显示方式:1只显示百分数,3只显示频率,2与NA则都显示
  4. show.n:默认FALSE,TRUE时显示该变量统计时用到的样本量
  5. show.descr:默认TRUE,显示统计描述
  6. show.all:默认FALSE,TRUE显示总的统计量,添加’ALL’这一列,非常有用!!
  7. show.p.overall,show.p.trend,show.p.mul显示对应统计P值,show.ratio显示OR或HR

2.3 createTable的print

Usage:

print(x, which.table = \"descr\", nmax = TRUE, header.labels = c(), ...)
  • which.table可取值’descr’, ‘avail’ or ‘both’,打印对应的统计表
  • header.labels更改显示的列名,可以更改:all’, ‘p.overall’, ‘p.trend’, ‘ratio’, ‘p.ratio’ and ‘N’, 方式为header.labels=c(p.overall=\"p-value\", all=\"ALL\")
  • nmax设定是否打印首行的样本量
>restab <- createTable(res)
>print(restab, which.table = \"descr\")
--------Summary descriptives table by \'Intervention group\'---------

________________________________________________________________________________ 
                               Control    MedDiet + Nuts MedDiet + VOO p.overall 
                                N=2042        N=2100        N=2182               
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 
Age                          67.3 (6.28)   66.7 (6.02)    67.0 (6.21)    0.003   
Sex:                                                                    <0.001   
    Male                     812 (39.8%)   968 (46.1%)    899 (41.2%)            
    Female                   1230 (60.2%)  1132 (53.9%)  1283 (58.8%)     
.................
>print(restab, which.table = \"avail\")

---Available data----

________________________________________________________________________________________________________ 
                            [ALL] Control MedDiet + Nuts MedDiet + VOO      method           select      
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 
Age                         6324   2042        2100          2182      continuous-normal       ALL       
Sex                         6324   2042        2100          2182         categorical          ALL           
Hormone-replacement therapy 3459   1174        1066          1219         categorical    sex == \"Female\" 
.......................

2.4 createTable的update

可以更新createTable, 同时也可更新compareGroups
示例:

update(restab, x = update(res, subset = c(sex == \"Female\")),     show.n = TRUE)

2.5 可以用的其它函数

  1. rbind,可以添加合并的标题:
restab1 <- createTable(compareGroups(group ~ age + sex, data = predimed))
restab2 <- createTable(compareGroups(group ~ bmi + smoke, data = predimed))
x=rbind(`Non-modifiable risk factors` = restab1, `Modifiable risk factors` = restab2)
# 选择部分变量
x[c(1,2,4)]
  1. cbind,合并列,可以分层
res <- compareGroups(group ~ age + smoke + bmi + htn, data = predimed)
alltab <- createTable(res, show.p.overall = FALSE)
femaletab <- createTable(update(res, subset = sex == \"Female\"),     show.p.overall = FALSE)
maletab <- createTable(update(res, subset = sex == \"Male\"), show.p.overall = FALSE)
# 合并
cbind(ALL = alltab, FEMALE = femaletab, MALE = maletab)
## caption参数定义每个层的标题
  1. strataTable,快速按变量分层
# usage:
strataTable(x, strata, strata.names = NULL, max.nlevels = 5)
# 示例
strataTable(restab, \"sex\")

2.6 一步构建表格:descrTable

Usage:

descrTable(formula, data, subset, na.action = NULL, y = NULL, Xext = NULL, 
  selec = NA, method = 1, timemax = NA, alpha = 0.05, min.dis = 5, max.ylev = 5, 
  max.xlev = 10, include.label = TRUE, Q1 = 0.25, Q3 = 0.75, simplify = TRUE, 
  ref = 1, ref.no = NA, fact.ratio = 1, ref.y = 1, p.corrected = TRUE, 
  compute.ratio = TRUE, include.miss = FALSE, oddsratio.method = \"midp\", 
  chisq.test.perm = FALSE, byrow = FALSE, chisq.test.B = 2000, chisq.test.seed = NULL,
  Date.format = \"d-mon-Y\", var.equal = TRUE, conf.level = 0.95, surv = FALSE,
  hide = NA, digits = NA, type = NA, show.p.overall = TRUE,
  show.all, show.p.trend, show.p.mul = FALSE, show.n, show.ratio =
  FALSE, show.descr = TRUE, show.ci = FALSE, hide.no = NA, digits.ratio = NA,
  show.p.ratio = show.ratio, digits.p = 3, sd.type = 1, q.type = c(1, 1),
  extra.labels = NA)

参数同createTable和compareGroups

3. 导出

3.1 函数

  • export2csv(restab, file=’table1.csv’)
  • export2html(restab, file=’table1.html’)
  • export2latex(restab, file=’table1.tex’)
  • export2pdf(restab, file=’table1.pdf’)
  • export2md(restab, file=’table1.md’)
  • export2word(restab, file=’table1.docx’)
  • export2xls(restab, file=’table1.xlsx’)

3.2 参数

  • which.table:同上
  • nmax:同上
  • sep: csv
  • 详细的参数见帮助文档

4. 缺失值处理

missingTable

missingTable(obj,...)

obj可以是’compareGroups’ or ‘createTable’ object,统计每个行变量的缺失在分组变量的情况

图形界面分析

cGroupsGUI(predimed)触发,详见说明文档,需要安装“tcltk2”包

Shiny应用

cGroupsWUI(),详见说明文档,需要安装“shinyBS”包

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