# HodgesLehmann

0th

Percentile

##### Hodges-Lehmann Estimator of Location

Function to compute the Hodges-Lehmann estimator of location in the one sample case. Simple wrapper to extract the value from the result of wilcox.test.

Keywords
robust, nonparametric, univar
##### Usage
HodgesLehmann(x, y = NULL, conf.level = NA, na.rm = FALSE)
##### Arguments
x
a numeric vector.
y
an optional numeric vector of data values: as with x non-finite values will be omitted.
conf.level
confidence level of.

na.rm
logical. Should missing values be removed? Defaults to FALSE.

##### Details

The Hodges-Lehmann estimator is the median of the combined data points and Walsh averages. It is the same as the Pseudo Median returned as a by-product of the function wilcox.test. Note that in the two-sample case the estimator for the difference in location parameters does not estimate the difference in medians (a common misconception) but rather the median of the difference between a sample from x and a sample from y. The confidence interval for the "pseudo median" is extracted from wilcox.test (conf.int = TRUE).

##### Value

the Hodges-Lehmann estimator of location as a single numeric value if no confidence intervals are requested, and otherwise a numeric vector with 3 elements for the estimate, the lower and the upper confidence interval

##### References

Hodges, J.L., and Lehmann, E.L. (1963), Estimates of location based on rank tests. The Annals of Mathematical Statistics, 34, 598--611.

wilcox.test, median, MedianCI

##### Aliases
• HodgesLehmann
##### Examples
set.seed(1)
x <- rt(100, df = 3)
HodgesLehmann(x)

# same as
wilcox.test(x,  conf.int = TRUE)\$estimate

Documentation reproduced from package DescTools, version 0.99.19, License: GPL (>= 2)

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