Re: [R] extracting bootstrap statistics by group with loop

Rui Barradas Sun, 31 Oct 2021 10:18:47 -0700

Hello,

Now I'm spamming the list, not one of my days.

My first post was right, there was no bug and the 2nd one was exactlythe same code, it corrected nothing at all.

Apologies for the noise,

Rui Barradas

Às 16:55 de 31/10/21, Rui Barradas escreveu:

Hello,

Sorry, bug. In both by instructions it's boot_mean_se, not bootprop.


boot_year <- by(DaT, DaT$Year, boot_mean_se, statistic = bootprop, R = R)
boot_year_area <- by(DaT,
                      INDICES = list(Year = DaT$Year, Area = DaT$Area),
                      FUN = boot_mean_se,
                      statistic = bootprop, R = R)


Hope this helps,

Rui Barradas

Às 16:48 de 31/10/21, Rui Barradas escreveu:

Hello,

Try to aggregate with ?by.


bootprop <- function(data, index){
   d <- data[index, ]
   sum(d[["bothTimes"]], na.rm = TRUE)/sum(d[["total"]], na.rm = TRUE)#
}
boot_mean_se <- function(data, statistic, R){
   b <- boot::boot(DaT, bootprop, R = R)
   c(bootMean = mean(b$t), bootSE = sd(b$t))
}

boot_year <- by(DaT, DaT$Year, boot_mean_se, statistic = bootprop, R = R)
boot_year_area <- by(DaT,
                      INDICES = list(Year = DaT$Year, Area = DaT$Area),
                      FUN = boot_mean_se,
                      statistic = bootprop, R = R)
boot_year
boot_year_area

boot_year <- do.call(rbind, boot_year)

d <- dimnames(boot_year_area)
boot_year_area <- cbind(Reduce(expand.grid, rev(d))[2:1],
                         do.call(rbind, boot_year_area))
names(boot_year_area)[1:2] <- names(d)
boot_year_area


Hope this helps,

Rui Barradas

Às 11:47 de 31/10/21, Marna Wagley escreveu:

Hi R users,

I was trying to extract the bootstrap mean and its SE by group but Ihave

been doing  it by separating the group manually. The data set is big so

doing it manually is a kind of tedious task. I am wondering whetherthere

is a possibility to do it by creating a loop. I am weak in writing loop
functions. I am attaching an example data and how I performed the
analysis, see below.
Thanks for your help.
Sincerely,
MW
####
library(boot)
DaT<-structure(list(bothTimes = c(0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L,
1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L),
total = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), Area = c("A",
"A", "A", "A", "A", "A", "B", "B", "B", "B", "B", "B", "A", "A",

"A", "A", "A", "A", "B", "B", "B", "B", "B", "B"), Year = c(2015L,2015L,

2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L, 2016L,
2016L, 2016L, 2016L, 2016L, 2016L)), class = "data.frame", row.names =
c(NA, -24L))

head(DaT)
R=100
bootprop <- function(data, index){
   d <- data[index, ]
   sum(d[["bothTimes"]], na.rm = TRUE)/sum(d[["total"]], na.rm = TRUE)#
}

###################
#2015
###################
#-----Year2015_pooled
Y2015_pooled<-subset(DaT, DaT$Year=="2015")
Y2015_pooled_boot <- boot(Y2015_pooled, bootprop, R)
boot_Y2015_pooled<-data.frame(Year="2015", Area= "Pooled", bootMean=
Y2015_pooled_boot$t0, SE=sd(Y2015_pooled_boot$t))
#-----Year2015_AreaA
Y2015_A<-subset(DaT, DaT$Year=="2015" & DaT$Area=="A")
Y2015_A_boot <- boot(Y2015_A, bootprop, R)

boot_Y2015_A<-data.frame(Year="2015", Area= "A", bootMean=Y2015_A_boot$t0,

SE=sd(Y2015_A_boot$t))
#----Year2015_AreaB
Y2015_B<-subset(DaT, DaT$Year=="2015" & DaT$Area=="B")
Y2015_B_boot <- boot(Y2015_B, bootprop, R)

boot_Y2015_B<-data.frame(Year="2015", Area= "B", bootMean=Y2015_B_boot$t0,

SE=sd(Y2015_B_boot$t))
###################
#2016
###################
#-----Year2016_pooled
Y2016_pooled<-subset(DaT, DaT$Year=="2016")
Y2016_pooled_boot <- boot(Y2016_pooled, bootprop, R)
boot_Y2016_pooled<-data.frame(Year="2016", Area= "Pooled", bootMean=
Y2016_pooled_boot$t0, SE=sd(Y2016_pooled_boot$t))

#-----Year2016_AreaA
Y2016_A<-subset(DaT, DaT$Year=="2016" & DaT$Area=="A")
Y2016_A_boot <- boot(Y2016_A, bootprop, R)

boot_Y2016_A<-data.frame(Year="2016", Area= "A", bootMean=Y2016_A_boot$t0,

SE=sd(Y2016_A_boot$t))
#----Year2016_AreaB
Y2016_B<-subset(DaT, DaT$Year=="2016" & DaT$Area=="B")
Y2016_B_boot <- boot(Y2016_B, bootprop, R)

boot_Y2016_B<-data.frame(Year="2016", Area= "B", bootMean=Y2016_B_boot$t0,

SE=sd(Y2016_B_boot$t))

## output data.matrix

BootMean_All<-rbind(boot_Y2015_pooled,boot_Y2015_A,boot_Y2015_B,boot_Y2016_pooled,boot_Y2016_A,boot_Y2016_B)

BootMean_All

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and provide commented, minimal, self-contained, reproducible code.

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Re: [R] extracting bootstrap statistics by group with loop

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