1

当使用文本而不是带标签的数字作为输入时，如何使用自定义表格显示显着差异？（在每个单元格中应该是 + 或 -）。

#Generate data
aw = function(n) { 
    sample(x = c("Aware","Consider","Buy"), n, replace = T, prob = c(0.1, 0.4, 0.5)) 
}
awa<-aw(3000)

gen = function(n) { 
    sample(x = c("Male","Female"), n, replace = T, prob = c(0.8, 0.2)) 
}
gende<-gen(3000)

ag = function(n) { 
    sample(x = c("<20","20 to 50","50+"), n, replace = T, prob = c(0.3, 0.2, 0.5)) 
}

age<-ag(3000)

data<-data.frame(awa,gende,age)
#Banner create
banner = calc(data, list(total(), gende,age))
#Custom table with significant differences calculated relative to total
data %>%
tab_significance_options(compare_type = "adjusted_first_column",subtable_marks = "both",sig_labels_first_column = c("-", "+"),mode = c("append")) %>%
tab_cells(awa) %>%
tab_cols(banner) %>%
tab_stat_cpct() %>%
tab_pivot()
4

1 回答 1

0

有一个函数tab_last_sig_cpct可以计算最后一个统计数据的显着性。统计数据应该是列百分比。

library(expss)
#Generate data
aw = function(n) { 
    sample(x = c("Aware","Consider","Buy"), n, replace = T, prob = c(0.1, 0.4, 0.5)) 
}
awa<-aw(3000)

gen = function(n) { 
    sample(x = c("Male","Female"), n, replace = T, prob = c(0.8, 0.2)) 
}
gende<-gen(3000)

ag = function(n) { 
    sample(x = c("<20","20 to 50","50+"), n, replace = T, prob = c(0.3, 0.2, 0.5)) 
}

age<-ag(3000)

data<-data.frame(awa,gende,age)
#Banner create
banner = calc(data, list(total(), gende,age))
#Custom table with significant differences calculated relative to total
data %>%
    tab_significance_options(compare_type = "adjusted_first_column",subtable_marks = "both",sig_labels_first_column = c("-", "+"),mode = c("append")) %>%
    tab_cells(awa) %>%
    tab_cols(banner) %>%
    tab_stat_cpct() %>%
    tab_last_sig_cpct(mode = "replace") %>% 
    tab_pivot()

 # |     |              | #Total | Female |   Male |    <20 | 20 to 50 |  50+ |
 # | --- | ------------ | ------ | ------ | ------ | ------ | -------- | ---- |
 # | awa |        Aware |   10.0 |  7.0 - | 10.8 + |  9.5   |     10.3 | 10.2 |
 # |     |          Buy |   51.1 | 53.8   | 50.4   | 48.6   |     51.4 | 52.5 |
 # |     |     Consider |   38.8 | 39.1   | 38.8   | 41.9 + |     38.3 | 37.3 |
 # |     | #Total cases |   3000 |  611   | 2389   |  884   |      601 | 1515 |
于 2019-03-15T09:18:00.937 回答