Trend tests in epidemiology: P-values or confidence intervals?

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

  • Ludwig A. Hothorn

Organisationseinheiten

Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)817-825
Seitenumfang9
FachzeitschriftBiometrical journal
Jahrgang41
Ausgabenummer7
PublikationsstatusVeröffentlicht - 9 Nov. 1999

Abstract

Frequently, p-values are used in reporting epidemiological trend data. Because a p-value is a confounded mixture of effect size and sample size in dichotomous data, LANG, ROTHMAN, and CANN (1998) recommended the slope of a trend line with its standard error and a graphical presentation containing the rate ratios as a function of mid-exposure levels. However, the slope contains the assumption of a dose-response function. This article discusses a proposal based on odds ratios and the corresponding one-sided lower confidence intervals for pair-wise comparisons ('exposure levels with zero exposure') as well as comparisons between incremental exposure levels. The proposed method allows both decisions on the global trend, the lowest-observed-adverse-effect-level (LOAEL) and the non-observed-adverse-effect-level (NOAEL), and a simple exploratory analysis.

ASJC Scopus Sachgebiete

Zitieren

Trend tests in epidemiology: P-values or confidence intervals? / Hothorn, Ludwig A.
in: Biometrical journal, Jahrgang 41, Nr. 7, 09.11.1999, S. 817-825.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Hothorn LA. Trend tests in epidemiology: P-values or confidence intervals? Biometrical journal. 1999 Nov 9;41(7):817-825. doi: 10.1002/(sici)1521-4036(199911)41:7<817::aid-bimj817>3.3.co;2-3
Hothorn, Ludwig A. / Trend tests in epidemiology : P-values or confidence intervals?. in: Biometrical journal. 1999 ; Jahrgang 41, Nr. 7. S. 817-825.
Download
@article{349860b6929c47fba90bea27dacea64f,
title = "Trend tests in epidemiology: P-values or confidence intervals?",
abstract = "Frequently, p-values are used in reporting epidemiological trend data. Because a p-value is a confounded mixture of effect size and sample size in dichotomous data, LANG, ROTHMAN, and CANN (1998) recommended the slope of a trend line with its standard error and a graphical presentation containing the rate ratios as a function of mid-exposure levels. However, the slope contains the assumption of a dose-response function. This article discusses a proposal based on odds ratios and the corresponding one-sided lower confidence intervals for pair-wise comparisons ('exposure levels with zero exposure') as well as comparisons between incremental exposure levels. The proposed method allows both decisions on the global trend, the lowest-observed-adverse-effect-level (LOAEL) and the non-observed-adverse-effect-level (NOAEL), and a simple exploratory analysis.",
keywords = "Dose-response analysis, Exposure study, LOAEL, NOAEL, Trend test",
author = "Hothorn, {Ludwig A.}",
year = "1999",
month = nov,
day = "9",
doi = "10.1002/(sici)1521-4036(199911)41:7<817::aid-bimj817>3.3.co;2-3",
language = "English",
volume = "41",
pages = "817--825",
journal = "Biometrical journal",
issn = "0323-3847",
publisher = "Wiley-VCH Verlag",
number = "7",

}

Download

TY - JOUR

T1 - Trend tests in epidemiology

T2 - P-values or confidence intervals?

AU - Hothorn, Ludwig A.

PY - 1999/11/9

Y1 - 1999/11/9

N2 - Frequently, p-values are used in reporting epidemiological trend data. Because a p-value is a confounded mixture of effect size and sample size in dichotomous data, LANG, ROTHMAN, and CANN (1998) recommended the slope of a trend line with its standard error and a graphical presentation containing the rate ratios as a function of mid-exposure levels. However, the slope contains the assumption of a dose-response function. This article discusses a proposal based on odds ratios and the corresponding one-sided lower confidence intervals for pair-wise comparisons ('exposure levels with zero exposure') as well as comparisons between incremental exposure levels. The proposed method allows both decisions on the global trend, the lowest-observed-adverse-effect-level (LOAEL) and the non-observed-adverse-effect-level (NOAEL), and a simple exploratory analysis.

AB - Frequently, p-values are used in reporting epidemiological trend data. Because a p-value is a confounded mixture of effect size and sample size in dichotomous data, LANG, ROTHMAN, and CANN (1998) recommended the slope of a trend line with its standard error and a graphical presentation containing the rate ratios as a function of mid-exposure levels. However, the slope contains the assumption of a dose-response function. This article discusses a proposal based on odds ratios and the corresponding one-sided lower confidence intervals for pair-wise comparisons ('exposure levels with zero exposure') as well as comparisons between incremental exposure levels. The proposed method allows both decisions on the global trend, the lowest-observed-adverse-effect-level (LOAEL) and the non-observed-adverse-effect-level (NOAEL), and a simple exploratory analysis.

KW - Dose-response analysis

KW - Exposure study

KW - LOAEL

KW - NOAEL

KW - Trend test

UR - http://www.scopus.com/inward/record.url?scp=0033432583&partnerID=8YFLogxK

U2 - 10.1002/(sici)1521-4036(199911)41:7<817::aid-bimj817>3.3.co;2-3

DO - 10.1002/(sici)1521-4036(199911)41:7<817::aid-bimj817>3.3.co;2-3

M3 - Article

AN - SCOPUS:0033432583

VL - 41

SP - 817

EP - 825

JO - Biometrical journal

JF - Biometrical journal

SN - 0323-3847

IS - 7

ER -