*! version 1.0.0 09apr2024

Title

rosner -- Rosner's generalized extreme studentized deviate (ESD) procedure to detect multiple outliers

Syntax

rosner varname [if] [in]
[,
k(#)
alpha(#) ]

k(#) maximum number of outliers to detect; default is k(1)

alpha(#) significance level; default is alpha(0.05)

by is allowed with rosner; see prefix.

Description

rosner implements Rosner's (1983) generalized extreme studentized deviate (ESD) procedure to test for up to k
potential outliers. Rosner's test has an advantage over some other procedures because it is designed to avoid "masking",
which occurs when an outlier goes undetected because it is close in value to another outlier.

Of note, Rosner (1983) indicates that this approximation does not work well for small samples (n < 25) and the
procedure's accuracy is still unknown when applied to non-normally distributed data.

Options

by(k) specifies the maximum number of potential outliers to detect. The default is k(1).

alpha(#) specifies the significance level; default is alpha(0.05).

Examples

Load example data (from Table 4 in Rosner [1983])

. use rosner_table4, clear

Assume a maximum of 10 potential outliers (Rosner [1983])

. rosner x, k(10)

Set alpha to 0.01

. rosner x, k(10) alpha(0.01)

References

Rosner, B. 1983. Percentage points for a generalized ESD many-outlier procedure. Technometrics 25: 165-172.

Citation of rosner

rosner is not an official Stata command. It is a free contribution
to the research community, like a paper. Please cite it as such:

Linden, Ariel. 2024. rosner: Stata module for implementing Rosner's generalized extreme studentized deviate (ESD)
procedure to detect multiple outliers.

Author

Ariel Linden

President, Linden Consulting Group, LLC

alinden@lindenconsulting.org

Also see

grubbs (if installed), obsofint (if installed)