Non-parametric two-sample tests for repeated ordinal responses

Michael P. Fay; Chris Gennings

doi:10.1002/(SICI)1097-0258(19960229)15:4<429::AID-SIM139>3.0.CO;2-I

Non-parametric two-sample tests for repeated ordinal responses

Michael P. Fay, Chris Gennings

Research output: Contribution to journal › Article › peer-review

7 Scopus citations

Abstract

Consider data on two groups of clusters, where each cluster consists of many units that respond on an ordinal scale. We develop a Mann-Whitney type test to determine whether a typical response from the first group is larger (or smaller) than a typical response from the second group.

Original language	English
Pages (from-to)	429-442
Number of pages	14
Journal	Statistics in Medicine
Volume	15
Issue number	4
DOIs	https://doi.org/10.1002/(SICI)1097-0258(19960229)15:4<429::AID-SIM139>3.0.CO;2-I
State	Published - 28 Feb 1996
Externally published	Yes

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10.1002/(SICI)1097-0258(19960229)15:4<429::AID-SIM139>3.0.CO;2-I

Cite this

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title = "Non-parametric two-sample tests for repeated ordinal responses",

abstract = "Consider data on two groups of clusters, where each cluster consists of many units that respond on an ordinal scale. We develop a Mann-Whitney type test to determine whether a typical response from the first group is larger (or smaller) than a typical response from the second group.",

author = "Fay, \{Michael P.\} and Chris Gennings",

year = "1996",

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AU - Gennings, Chris

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AB - Consider data on two groups of clusters, where each cluster consists of many units that respond on an ordinal scale. We develop a Mann-Whitney type test to determine whether a typical response from the first group is larger (or smaller) than a typical response from the second group.

UR - https://www.scopus.com/pages/publications/0030028858

U2 - 10.1002/(SICI)1097-0258(19960229)15:4<429::AID-SIM139>3.0.CO;2-I

DO - 10.1002/(SICI)1097-0258(19960229)15:4<429::AID-SIM139>3.0.CO;2-I

M3 - Article

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EP - 442

JO - Statistics in Medicine

JF - Statistics in Medicine

IS - 4

ER -

Non-parametric two-sample tests for repeated ordinal responses

Abstract

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