R：使用dplyr函数创建函数

Question

I have a data frame with three variables of interest:

• survival time
• grouping factor
• event indicator (dead: yes or no)

I want to calculate incidence rate for each group. I do this daily, so it would be great to have a function doing this instead of a long script.

I've tried the following, but doesn't work.

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'**

Any ideas? I've read the post about NSE and SE in dplyr, but thought I applied the recommendations correctly?

Answer 1

Here is a part of the solution

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, ")")
  )