如果这个问题重复或已经在其他地方问过,我深表歉意。
我喜欢用这种格式创建汇总表。
1) Discrete variables : n/N (%)
2a) Continuous variables : mean (SD); N
2b) Continuous variables : median (IQR); N
例如,如果这是我的数据
# Example dataset
set.seed(123)
data <- data.frame(
ChildSex = sample(c("Male", "Female"), 5006, replace = TRUE),
col1 = rnorm(5006, mean = 300, sd = 100),
col2 = rnorm(5006, mean = 400, sd = 150),
col3 = rnorm(5006, mean = 470, sd = 200)
)
预期的摘要应该是这样的
Discrete Variables
Child sex
Male 2505/5006 (50%)
Female 2501/5006 (50%)
Data missing 0 /5006 (0%)
Continuous Variables: mean (SD); N
Col1 299.90 (99.38); 5006
Col2 399.12 (151.530); 5006
Continuous Variables: median (IQR); N
Col3 465.85 (268.15); 5006
我有大约 20 个离散变量和 30 个连续变量(18 个均值、标准差和 12 个中位数、IQR)。我喜欢创建如上所示的汇总表,而无需手动输入变量名称或级别。感谢您提前提供任何建议或建议..
set.seed(123)
data <- data.frame(
ChildSex = c(sample(c("Male", "Female"), 5005, replace = TRUE), NA),
col1 = rnorm(5006, mean = 300, sd = 100),
col2 = rnorm(5006, mean = 400, sd = 150),
col3 = rnorm(5006, mean = 470, sd = 200)
)
data
tbl_summary(data,
type=list(col1="continuous2",
col2="continuous2",
col3="continuous2"),
statistic = list(c(col1,col2) ~ "{mean} ({sd})",
col3 ~ "{median} ({p25}-{p75})",
all_categorical() ~"{n}/{N_obs} ({p}%)"),
missing="ifany",
missing_text = "Data missing",
missing_stat = "{N_miss} / {N_obs} ({p_miss}%))")
给予