如何使用测量权重在R汇总表中创建子视图

如何使用测量权重在R汇总表中创建子视图,r,datatable,row,cluster-analysis,R,Datatable,Row,Cluster Analysis,我想创建一个汇总统计表,该表按地区报告每个变量的平均值/中位数,并在行中比较样本中美国出生和移民的统计数据以及总体数据。我不知道哪些代码可以让我以多种方式对表进行分组 以下是我迄今为止提出的代码: #the data frame structure(list(AGE = c(40L, 23L, 24L, 18L, 30L, 33L, 32L, 63L, 22L, 24L), FAMSIZE = c(2L, 2L, 2L, 3L, 2L, 6L, 2L, 1L, 2L, 1L ), HYPER

我想创建一个汇总统计表,该表按地区报告每个变量的平均值/中位数,并在行中比较样本中美国出生和移民的统计数据以及总体数据。我不知道哪些代码可以让我以多种方式对表进行分组

以下是我迄今为止提出的代码:

#the data frame 
structure(list(AGE = c(40L, 23L, 24L, 18L, 30L, 33L, 32L, 63L, 
22L, 24L), FAMSIZE = c(2L, 2L, 2L, 3L, 2L, 6L, 2L, 1L, 2L, 1L
), HYPERTEN = c(0, 0, 0, 0, 0, 0, 0, 1, 0, 0), ALC = c(0, 2, 
3, 0, 2, 0, 3, 0, 2, 2), region_group = c("Region 4", "Region 3", 
"Region 4", "Region 3", "Region 1", "Region 2", "Region 1", "Region 2", 
"Region 4", "Region 4"), PSU = c(2L, 1L, 2L, 2L, 2L, 1L, 2L, 
2L, 1L, 2L), IMMIGRANT = c(0, 0, 0, 0, 0, 1, 0, 0, 0, 1), SAMPWEIGHT_MERGE = c(65, 860.4, 
94.4, 9146, 170.8, 310.4, 755.2, 1053.4, 3964.4, 706.2), STRATA = c(6296L, 
6165L, 6296L, 6224L, 6045L, 6083L, 6029L, 6073L, 6287L, 6247L
)), row.names = c(NA, 10L), class = "data.frame") 
 
#weighting data frame so accounts for sample design
sample_survey<- as_survey_design(A, ids=PSU, weights=SAMPWEIGHT_MERGE, strata=STRATA, nest=TRUE) 
options(survey.lonely.psu="remove")

#producing desired table 
out1<-sample_survey %>% 
  group_by(region_group) %>% 
  summarise("Number of drinks (mean)"=survey_mean(ALC),
            "Number of drinks (median)"=survey_median(ALC),"Hypertension"=survey_mean(HYPERTEN), "Family Size"=survey_mean(FAMSIZE), "Age"=survey_median(AGE))

out1=t(out1) 
out1

#But here is what I hope the table can look like, such that the mean/median amongst all individuals, immigrant=0 and the immigrant=1 group are all displayed for each variable 

                           [,1]         [,2]         [,3]         [,4]        
region_group                 "Region 1"   "Region 2"   "Region 3"   "Region 4"  
Number of drinks (all)      "1.663778"   "2.131566"   "1.744107"   "2.009594"  
   IMMIGRANT==0                 
   IMMIGRANT==1  
Number of drinks (mean)_se   "0.1375124"  "0.1245772"  "0.0957500"  "0.1199982" 
Number of drinks (all)         "1"          "2"          "1"          "2"
   IMMIGRANT==0                 
   IMMIGRANT==1           
Number of drinks (median)_se "0.0000000"  "0.2531528"  "0.0000000"  "0.2533324" 
Hypertension  (all)           "0.1340147"  "0.1685102"  "0.1834528"  "0.1225418" 
   IMMIGRANT==0                 
   IMMIGRANT==1 
Hypertension_se              "0.01623974" "0.01529678" "0.01463019" "0.01475651"
Family \n    (all)        Size    "3.121062"   "2.883905"   "3.107202"   "3.265012"  
   IMMIGRANT==0                 
   IMMIGRANT==1 
Family \n            Size_se "0.11668906" "0.07435704" "0.08004129" "0.11138869"
Age      (all)                    "30"         "27"         "30"         "28"        
   IMMIGRANT==0                 
   IMMIGRANT==1 
Age_se                       "1.3615690"  "1.0126110"  "0.7616152"  "0.7599972" 
#数据帧
结构(列表)年龄=c(40L、23L、24L、18L、30L、33L、32L、63L、,
22L,24L),FAMSIZE=c(2L,2L,2L,3L,2L,6L,2L,1L,2L,1L
),HYPERTEN=c(0,0,0,0,0,0,0,1,0,0,0),ALC=c(0,2,
3,0,2,0,3,0,2,2),区域组=c(“区域4”,“区域3”,
“第4区”、“第3区”、“第1区”、“第2区”、“第1区”、“第2区”,
“区域4”,“区域4”),PSU=c(2L,1L,2L,2L,2L,1L,2L,
2L,1L,2L),移民=c(0,0,0,0,0,1,0,0,0,1),样本重量=c(65860.4,
94.49146170.8310.4755.21053.43964.4706.2),地层=c(6296L,
6165L、6296L、6224L、6045L、6083L、6029L、6073L、6287L、6247L
)),row.names=c(NA,10L),class=“data.frame”)
#对数据帧进行加权,以便考虑样本设计
抽样调查%
总结(“饮料数量(平均值)”=调查平均值(ALC),
“饮酒量(中位数)”=调查中位数(ALC),“高血压”=调查中位数(高血压),“家庭规模”=调查中位数(家庭规模),“年龄”=调查中位数(年龄))
out1=t(out1)
out1
#但这是我希望表格的样子,这样所有个体的平均值/中位数,移民=0和移民=1组都会显示每个变量
[,1]         [,2]         [,3]         [,4]        
区域组“区域1”“区域2”“区域3”“区域4”
饮品数目(全部)“1.663778”“2.131566”“1.744107”“2.009594”
移民==0
移民==1
饮料数量(平均值)_se“0.1375124”“0.1245772”“0.0957500”“0.1199982”
饮料数量(全部)“1”“2”“1”“2”
移民==0
移民==1
饮品数量(中位数)\ u使用“0.0000000”“0.2531528”“0.0000000”“0.253324”
高血压(全部)“0.1340147”“0.1685102”“0.1834528”“0.1225418”
移民==0
移民==1
高血压患者使用“0.01623974”“0.01529678”“0.01463019”“0.01475651”
系列\n(全部)尺寸“3.121062”“2.883905”“3.107202”“3.265012”
移民==0
移民==1
系列尺寸为“0.11668906”“0.07435704”“0.08004129”“0.11138869”
年龄(全部)“30”“27”“30”“28”
移民==0
移民==1
年龄为“1.3615690”“1.0126110”“0.7616152”“0.7599972”
谢谢大家!

您可以使用:

您可以使用:


@哦,对不起!谢谢你指出这一点,不知怎的,一个逗号漏掉了。应该运行正常now@akrun哎呀,对不起!谢谢你指出这一点,不知怎的,一个逗号漏掉了。现在应该正常运行了好的,谢谢你的建议。虽然我想知道这是否意味着/中位数占了调查权重?代码如何创建一个多变量表(即高血压、年龄)?我添加了HYPERTEN作为一个新变量的示例。看看如何考虑权重OK非常感谢!虽然这有点棘手,因为高血压是一个二元变量(个体有或没有),所以我不需要/不想计算该变量的中位数。请参阅我的编辑,您可以将
参数(w=SAMPWEIGHT\u MERGE)
传递到
加权。平均值
好,这很有意义!谢谢你调查此事。有没有办法计算加权中值呢?好的,谢谢你的想法。虽然我想知道这是否意味着/中位数占了调查权重?代码如何创建一个多变量表(即高血压、年龄)?我添加了HYPERTEN作为一个新变量的示例。看看如何考虑权重OK非常感谢!虽然这有点棘手,因为高血压是一个二元变量(个体有或没有),所以我不需要/不想计算该变量的中位数。请参阅我的编辑,您可以将
参数(w=SAMPWEIGHT\u MERGE)
传递到
加权。平均值
好,这很有意义!谢谢你调查此事。有没有办法计算加权中值呢?
library(tables)
tables::tabular((ALC+HYPERTEN)*(IMMIGRANT=factor(IMMIGRANT)+1)*(weighted.mean+median)*Arguments(w = SAMPWEIGHT_MERGE)~(region=factor(region_group)), data=data)

                                 region                    
          IMMIGRANT               Region 1 Region 2 Region 3
 ALC      0         weighted.mean 2.816    0.0000   0.172   
                    median        2.500    0.0000   1.000   
          1         weighted.mean   NaN    0.0000     NaN   
                    median           NA    0.0000      NA   
          All       weighted.mean 2.816    0.0000   0.172   
                    median        2.500    0.0000   1.000   
 HYPERTEN 0         weighted.mean 0.000    1.0000   0.000   
                    median        0.000    1.0000   0.000   
          1         weighted.mean   NaN    0.0000     NaN   
                    median           NA    0.0000      NA   
          All       weighted.mean 0.000    0.7724   0.000   
                    median        0.000    0.5000   0.000