[英]In R, apply a sequence of complex functions using the “do” function in dplyr
[英]R: Creating a function using dplyr functions
我有一个包含三个感兴趣变量的数据框:
我想计算每个组的发生率。 我每天都这样做,所以有一个函数来执行此操作而不是冗长的脚本将是很棒的。
我已经尝试了以下方法,但是不起作用。
library(survival)
data(lung) # example data
lung$death <- ifelse(lung$status==1, 0, 1) # event indicator: 0 = survived; 1 = dead.
# Function
func <- function(data_frame, group, survival_time, event) {
library(epitools)
table <- data_frame %>%
filter_(!is.na(.$group)) %>%
group_by_(.$group) %>%
summarise_(pt = round(sum(as.numeric(.$survival_time)/365.25)),
events = sum(.$event)) %>%
do(pois.exact(.$events, pt = .$pt/1000, conf.level = 0.95)) %>%
ungroup() %>%
transmute_(Category = c(levels(as.factor(.$group))),
Events = x,
Person_years = pt*1000,
Incidence_Rate = paste(format(round(rate, 2), nsmall=2), " (",
format(round(lower, 2), nsmall=2), " to ",
format(round(upper, 2), nsmall=2), ")",
sep=""))
return(table)
}
func(lung, sex, time, death)
**Error: incorrect length (0), expecting: 228 In addition: Warning message:
In is.na(.$group) : is.na() applied to non-(list or vector) of type 'NULL'**
有任何想法吗? 我已经在dplyr中阅读了有关NSE和SE的帖子,但以为我正确应用了建议?
这是解决方案的一部分
data_frame = lung
group = "sex"
survival_time = "time"
event = "death"
data_frame %>%
filter_(paste("!is.na(", group, ")")) %>%
group_by_(group) %>%
summarise_(
pt = paste("round(sum(as.numeric(", survival_time, ") / 365.25))"),
events = paste("sum(", event, ")")
)
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