Testing longitudinal data by logarithmic quantiles

Manfred Denker; Lucia Tabacu

doi:10.1214/14-EJS965

Testing longitudinal data by logarithmic quantiles

Manfred Denker
, Lucia Tabacu

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

2 Scopus citations

Abstract

The shoulder tip pain study of Lumley [13] is re-investigated. It is shown that the new logarithmic quantile estimation (LQE) technique in [9] applies and behaves well under singular covariance structure and small sample sizes as in the shoulder tip pain study. The findings in [6] can be assured under weaker assumptions using a combination of LQE and an ANOVA type statistic.

Original language	English (US)
Pages (from-to)	2937-2952
Number of pages	16
Journal	Electronic Journal of Statistics
Volume	8
DOIs	https://doi.org/10.1214/14-EJS965
State	Published - 2014

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1214/14-EJS965

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title = "Testing longitudinal data by logarithmic quantiles",

abstract = "The shoulder tip pain study of Lumley [13] is re-investigated. It is shown that the new logarithmic quantile estimation (LQE) technique in [9] applies and behaves well under singular covariance structure and small sample sizes as in the shoulder tip pain study. The findings in [6] can be assured under weaker assumptions using a combination of LQE and an ANOVA type statistic.",

author = "Manfred Denker and Lucia Tabacu",

year = "2014",

doi = "10.1214/14-EJS965",

language = "English (US)",

volume = "8",

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AU - Denker, Manfred

AU - Tabacu, Lucia

PY - 2014

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AB - The shoulder tip pain study of Lumley [13] is re-investigated. It is shown that the new logarithmic quantile estimation (LQE) technique in [9] applies and behaves well under singular covariance structure and small sample sizes as in the shoulder tip pain study. The findings in [6] can be assured under weaker assumptions using a combination of LQE and an ANOVA type statistic.

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UR - https://www.scopus.com/pages/publications/84939530761#tab=citedBy

U2 - 10.1214/14-EJS965

DO - 10.1214/14-EJS965

M3 - Article

AN - SCOPUS:84939530761

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VL - 8

SP - 2937

EP - 2952

JO - Electronic Journal of Statistics

JF - Electronic Journal of Statistics

ER -

Testing longitudinal data by logarithmic quantiles

Abstract

All Science Journal Classification (ASJC) codes

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