多列联系表

• table()生成多维列表

> mytable <- xtabs(~ Treatment+Sex+Improved, data=Arthritis)  
> mytable
, , Improved = None

         Sex
Treatment Female Male
  Placebo     19   10
  Treated      6    7

, , Improved = Some

         Sex
Treatment Female Male
  Placebo      7    0
  Treated      5    2

, , Improved = Marked

         Sex
Treatment Female Male
  Placebo      6    1
  Treated     16    5

• ftable()

生成一种紧凑而吸引人的方式输出多维列联表

> ftable(mytable)    #将mytable做为参数传入fatable()
                 Improved None Some Marked
Treatment Sex                             
Placebo   Female            19    7      6
          Male              10    0      1
Treated   Female             6    5     16
          Male               7    2      5

 

• 边际及比例计算

> margin.table(mytable, 1)    #计算第一个变量 Treatment的边际频数（即求个数和）
Treatment
Placebo Treated 
     43      41 
> margin.table(mytable, 2)
Sex
Female   Male 
    59     25 
> margin.table(mytable, 2)
Sex
Female   Male 
    59     25 
> margin.table(mytable, c(1,3))  # 计算Treatment*Improved分组的边际频数
         Improved
Treatment None Some Marked
  Placebo   29    7      7
  Treated   13    7     21
> ftable(prop.table(mytable, c(1,2)))  #计算Treatment*Sex组合中改善状况为None，Some和Marked的比例
                 Improved       None       Some     Marked
Treatment Sex                                             
Placebo   Female          0.59375000 0.21875000 0.18750000
          Male            0.90909091 0.00000000 0.09090909
Treated   Female          0.22222222 0.18518519 0.59259259
          Male            0.50000000 0.14285714 0.35714286
> ftable(addmargins(prop.table(mytable, c(1, 2)), 3))  #乘以100，获得百分比而不是比例
                 Improved       None       Some     Marked        Sum
Treatment Sex                                                        
Placebo   Female          0.59375000 0.21875000 0.18750000 1.00000000
          Male            0.90909091 0.00000000 0.09090909 1.00000000
Treated   Female          0.22222222 0.18518519 0.59259259 1.00000000
          Male            0.50000000 0.14285714 0.35714286 1.00000000