[R] How to generate SE for the proportion value using a randomization process in R?

Rui Barradas ru|pb@rr@d@@ @end|ng |rom @@po@pt
Sat Jan 23 00:07:05 CET 2021


Hello,

Something like this, using base package boot?


library(boot)

bootprop <- function(data, index){
   d <- data[index, ]
   sum(d[["BothTimes"]], na.rm = TRUE)/sum(d[["Time1"]], na.rm = TRUE)
}

R <- 1e3
set.seed(2020)
b <- boot(daT, bootprop, R)
b
b$t0     # original
sd(b$t)  # bootstrapped estimate of the SE of the sample prop.
hist(b$t, freq = FALSE)


Hope this helps,

Rui Barradas

Às 21:57 de 22/01/21, Marna Wagley escreveu:
> Hi All,
> I was trying to estimate standard error (SE) for the proportion value using
> some kind of randomization process (bootstrapping or jackknifing) in R, but
> I could not figure it out.
> 
> Is there any way to generate SE for the proportion?
> 
> The example of the data and the code I am using is attached for your
> reference. I would like to generate the value of proportion with a SE using
> a 1000 times randomization.
> 
> dat<-structure(list(Sample = structure(c(1L, 12L, 13L, 14L, 15L, 16L,
> 17L, 18L, 19L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L), .Label = c("id1",
> "id10", "id11", "id12", "id13", "id14", "id15", "id16", "id17",
> "id18", "id19", "Id2", "id3", "id4", "id5", "id6", "id7", "id8",
> "id9"), class = "factor"), Time1 = c(0L, 1L, 1L, 1L, 0L, 0L,
> 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L), Time2 = c(1L,
> 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L,
> 1L, 1L)), .Names = c("Sample", "Time1", "Time2"), class = "data.frame",
> row.names = c(NA,
> -19L))
> daT<-data.frame(dat %>%
>    mutate(Time1.but.not.in.Time2 = case_when(
>              Time1 %in% "1" & Time2 %in% "0"  ~ "1"),
> Time2.but.not.in.Time1 = case_when(
>              Time1 %in% "0" & Time2 %in% "1"  ~ "1"),
>   BothTimes = case_when(
>              Time1 %in% "1" & Time2 %in% "1"  ~ "1")))
>   daT
>   summary(daT)
> 
> cols.num <- c("Time1.but.not.in.Time2","Time2.but.not.in.Time1",
> "BothTimes")
> daT[cols.num] <- sapply(daT[cols.num],as.numeric)
> summary(daT)
> ProportionValue<-sum(daT$BothTimes, na.rm=T)/sum(daT$Time1, na.rm=T)
> ProportionValue
> standard error??
> 
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> 
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