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rloopsfor-loopstatisticsconfidence-interval
Kate Mahony
Kate Mahony

Reputation: 13

Looking for a way to loop through columns of a dataset to calculate multiple confidence intervals (to be inserted to a new column)

I am calculating confidence intervals in R from the PropCIs package. So far I am calculating these all individually, separately running the exactci function and manually extracting the upper and lower confidence intervals. This is very time consuming considering I have a large dataset.

I imagine a loop would help make this straightforward but I would appreciate advice on how to execute this.

So far, here is my code:

#Creating a dummy data frame
success<-c(5,20,30)
n<-c(300,300,300)
data<-data.frame(success, n)

#Here I have been manually entering the data to the exactci function
library(PropCIs)
exactci(5,300, conf.level=0.95)
exactci(20,300, conf.level=0.95)
exactci(30,300, conf.level=0.95)

How would I conduct this using a loop, while also adding two extra columns to my dataframe to store the output (upper and lower confidence intervals)?

Upvotes: 1

Views: 399

Answers (2)

Chuck P
Chuck P

Reputation: 3923

Since exactci produces an htest object, you can also use broom and purrr

library(purrr)
library(broom)
library(PropCIs)

map2_df(.x = data$success,
        .y = data$n,
        ~ broom::tidy(exactci(.x,
                              .y,
                              conf.level = .95)
        )) %>% 
   cbind(data, .)
#>   success   n    conf.low  conf.high
#> 1       5 300 0.005433205 0.03846374
#> 2      20 300 0.041194016 0.10108565
#> 3      30 300 0.068491684 0.13967331

Your data

data <- data.frame(success = c(5,20,30), 
                   n = c(300,300,300)
                   )

Upvotes: 0

Ronak Shah
Ronak Shah

Reputation: 389047

You can use any of the apply* loop :

library(PropCIs)
data[c('lower.ci', 'upper.ci')] <- t(mapply(function(x, y) 
        exactci(x,y, conf.level=0.95)$conf.int, data$success, data$n))
data

#  success   n lower.ci upper.ci
#1       5 300 0.005433  0.03846
#2      20 300 0.041194  0.10109
#3      30 300 0.068492  0.13967

Upvotes: 1

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