我使用
library(tableone)
对多个变量进行描述性统计
这是我的代码:
library(tableone)
myVars <- c("class", "age", "Sex", "bmi", "bmi_category",
"drink_freq", "smoke_yn", "edu_dummy")
catVars <- c("class", "Sex", "bmi_category",
"drink_freq", "smoke_yn", "edu_dummy")
tab1_inf <- CreateTableOne(vars = myVars, strata = "NEWDI",
data = TKA_table1, factorVars = catVars)
a1 <- print(tab1_inf, exact = "NEWDI", showAllLevels = TRUE)
我检查了它的描述,发现没有可以设置的选项。 https://rdrr.io/cran/tableone/man/print.TableOne.html 我该怎么办?
通过一些巧妙的动手操作,您可以操纵 TableOne 对象中的百分比。这使用来自
pbc
包的名为 survival
的示例数据集。
library(tableone)
library(survival)
data(pbc)
## Make categorical variables factors
varsToFactor <- c("status","trt","ascites","hepato","spiders","edema","stage")
pbc[varsToFactor] <- lapply(pbc[varsToFactor], factor)
## Create a variable list
vars <- c("time","status","age","sex","ascites","hepato",
"spiders","edema","bili","chol","albumin",
"copper","alk.phos","ast","trig","platelet",
"protime","stage")
## Create Table 1 stratified by trt
tableOne <- CreateTableOne(vars = vars, strata = c("trt"), data = pbc)
tableOne
之前
Stratified by trt
1 2 p test
n 158 154
time (mean (SD)) 2015.62 (1094.12) 1996.86 (1155.93) 0.883
status (%) 0.894
0 83 (52.5) 85 (55.2)
1 10 ( 6.3) 9 ( 5.8)
2 65 (41.1) 60 (39.0)
age (mean (SD)) 51.42 (11.01) 48.58 (9.96) 0.018
sex = f (%) 137 (86.7) 139 (90.3) 0.421
ascites = 1 (%) 14 ( 8.9) 10 ( 6.5) 0.567
hepato = 1 (%) 73 (46.2) 87 (56.5) 0.088
spiders = 1 (%) 45 (28.5) 45 (29.2) 0.985
...
您应该尝试根据您自己的数据格式调整以下代码:
for (i in 1:length(table1)) {
sum = tableOne$CatTable[[1]][[i]]$freq + tableOne$CatTable[[2]][[i]]$freq
tableOne$CatTable[[1]][[i]]$percent = tableOne$CatTable[[1]][[i]]$freq / sum
tableOne$CatTable[[2]][[i]]$percent = tableOne$CatTable[[2]][[i]]$freq / sum
}
}
tableOne
之后
Stratified by trt
1 2 p test
n 158 154
time (mean (SD)) 2015.62 (1094.12) 1996.86 (1155.93) 0.883
status (%) 0.894
0 83 (0.5) 85 (0.5)
1 10 (0.5) 9 (0.5)
2 65 (0.5) 60 (0.5)
age (mean (SD)) 51.42 (11.01) 48.58 (9.96) 0.018
sex = f (%) 137 (0.5) 139 (0.5) 0.421
ascites = 1 (%) 14 (0.6) 10 (0.4) 0.567
hepato = 1 (%) 73 (0.5) 87 (0.5) 0.088
spiders = 1 (%) 45 (0.5) 45 (0.5) 0.985
你是如何解决这个问题的?上面的解决方案对我不起作用,而且似乎对 Vons 也不起作用(全部填充到 0.5)?我可能会遗漏一些东西,但是......?
我还没有50声望,所以我无法发表评论,但这应该是一个评论。