R: Confidence Interval for the Median

MedianCI {DescTools} | R Documentation

## Confidence Interval for the Median

### Description

Calculates the confidence interval for the median.

### Usage

    MedianCI(x, conf.level = 0.95, sides = c("two.sided", "left", "right"),
             na.rm = FALSE, method = c("exact", "boot"), R = 999)

### Arguments

`x` | a (non-empty) numeric vector of data values.
`conf.level` | confidence level of the interval
`sides` | a character string specifying the side of the confidence interval, must be one of `"two.sided"` (default), `"left"` or `"right"`. You can specify just the initial letter. `"left"` would be analogue to a hypothesis of `"greater"` in a `t.test`.
`na.rm` | logical. Should missing values be removed? Defaults to `FALSE`.
`method` | defining the type of interval that should be calculated (one out of `"exact"`, `"boot"`). Default is `"exact"`. See Details.
`R` | The number of bootstrap replicates. Usually this will be a single positive integer. See `boot.ci` for details.

### Details

The exact method is the way SAS is said to calculate the confidence interval. This is implemented in `SignTest` and is extracted from there. The boot confidence interval type is calculated by means of `boot.ci` with default type `"basic"`.
Use `sapply`, resp.`apply`, to get the confidence intervals from a data.frame or from a matrix.

### Value

a numeric vector with 3 elements:

`median` | median
`lwr.ci` | lower bound of the confidence interval
`upr.ci` | upper bound of the confidence interval

### Author(s)

Andri Signorell <andri@signorell.net>

### See Also

`wilcox.test`, `MeanCI`, `median`, `HodgesLehmann`

### Examples

    MedianCI(d.pizza$price, na.rm=TRUE)
    MedianCI(d.pizza$price, conf.level=0.99, na.rm=TRUE)

    t(round(sapply(d.pizza[,c("delivery_min","temperature","price")], MedianCI, na.rm=TRUE), 3))

    MedianCI(d.pizza$price, na.rm=TRUE, method="exact")
    MedianCI(d.pizza$price, na.rm=TRUE, method="boot")

[Package DescTools version 0.99.25 Index]