The goal of citools is to …
Installation
You can install the development version of citools from GitHub with:
# install.packages("devtools")
devtools::install_github("GSK-Biostatistics/citools")Example
This is a basic example which shows you how to solve a common problem:
library(citools)
# Example of CI for proportions
x <- c(
TRUE, TRUE, TRUE, TRUE, TRUE,
FALSE, FALSE, FALSE, FALSE, FALSE
)
ci_prop_wald(x, conf.level = 0.9)
#> $N
#> [1] 10
#>
#> $n
#> [1] 5
#>
#> $estimate
#> [1] 0.5
#>
#> $conf.low
#> [1] 0.2399258
#>
#> $conf.high
#> [1] 0.7600742
#>
#> $conf.level
#> [1] 0.9
#>
#> $method
#> Wald Confidence Interval without continuity correction
ci_prop_wilson(x, correct = TRUE)
#> $N
#> [1] 10
#>
#> $n
#> [1] 5
#>
#> $conf.level
#> [1] 0.95
#>
#> $estimate
#> p
#> 0.5
#>
#> $statistic
#> X-squared
#> 0
#>
#> $p.value
#> [1] 1
#>
#> $parameter
#> df
#> 1
#>
#> $conf.low
#> [1] 0.2365931
#>
#> $conf.high
#> [1] 0.7634069
#>
#> $method
#> Wilson Confidence Interval with continuity correction
#>
#> $alternative
#> [1] "two.sided"
ci_prop_clopper_pearson(x)
#> $N
#> [1] 10
#>
#> $n
#> [1] 5
#>
#> $conf.level
#> [1] 0.95
#>
#> $estimate
#> probability of success
#> 0.5
#>
#> $statistic
#> number of successes
#> 5
#>
#> $p.value
#> [1] 1
#>
#> $parameter
#> number of trials
#> 10
#>
#> $conf.low
#> [1] 0.187086
#>
#> $conf.high
#> [1] 0.812914
#>
#> $method
#> [1] "Clopper-Pearson Confidence Interval"
#>
#> $alternative
#> [1] "two.sided"
ci_prop_agresti_coull(x)
#> $N
#> [1] 10
#>
#> $n
#> [1] 5
#>
#> $estimate
#> [1] 0.5
#>
#> $conf.low
#> [1] 0.2365931
#>
#> $conf.high
#> [1] 0.7634069
#>
#> $conf.level
#> [1] 0.95
#>
#> $method
#> [1] "Agresti-Coull Confidence Interval"
ci_prop_jeffreys(x)
#> $N
#> [1] 10
#>
#> $n
#> [1] 5
#>
#> $estimate
#> [1] 0.5
#>
#> $conf.low
#> [1] 0.2235287
#>
#> $conf.high
#> [1] 0.7764713
#>
#> $conf.level
#> [1] 0.95
#>
#> $method
#> Jeffreys Interval
# Example of CI for difference of proportions
# Generate binary samples
responses <- expand(c(9, 3), c(10, 10))
arm <- rep(c("treat", "control"), times = c(10, 10))
# Calculate 95% confidence interval for difference in proportions
ci_prop_diff_mn(x = responses, by = arm)
#> $estimate
#> [1] -0.6
#>
#> $conf.low
#> [1] -0.8406495
#>
#> $conf.high
#> [1] -0.170025
#>
#> $conf.level
#> [1] 0.95
#>
#> $delta
#> NULL
#>
#> $statistic
#> NULL
#>
#> $p.value
#> NULL
#>
#> $method
#> Miettinen-Nurminen Confidence Interval