Cox regression survival analysis with compositional covariates: Application to modelling mortality risk from 24-h physical activity patterns

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F20%3A73604803" target="_blank" >RIV/61989592:15310/20:73604803 - isvavai.cz</a>

Result on the web

<a href="https://obd.upol.cz/id_publ/333184689" target="_blank" >https://obd.upol.cz/id_publ/333184689</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1177/0962280219864125" target="_blank" >10.1177/0962280219864125</a>

Result language

angličtina

Original language name

Cox regression survival analysis with compositional covariates: Application to modelling mortality risk from 24-h physical activity patterns

Original language description

Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular statistical tool used in this context. However, when the exposure includes compositional covariables (that is, variables representing a relative makeup such as a nutritional or physical activity behaviour composition), some basic assumptions of the Cox regression model and associated significance tests are violated. Compositional variables involve an intrinsic interplay between one another which precludes results and conclusions based on considering them in isolation as is ordinarily done. In this work, we introduce a formulation of the Cox regression model in terms of log-ratio coordinates which suitably deals with the constraints of compositional covariates, facilitates the use of common statistical inference methods, and allows for scientifically meaningful interpretations. We illustrate its practical application to a public health problem: the estimation of the mortality hazard associated with the composition of daily activity behaviour (physical activity, sitting time and sleep) using data from the U.S. National Health and Nutrition Examination Survey (NHANES).

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GA18-09188S" target="_blank" >GA18-09188S: Application of a novel compositional data analysis approach for the evaluation of combined effects of 24-hour lifestyle behaviors on childhood obesity</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2020

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

STATISTICAL METHODS IN MEDICAL RESEARCH

ISSN

0962-2802

e-ISSN

—

Volume of the periodical

29

Issue of the periodical within the volume

5

Country of publishing house

GB - UNITED KINGDOM

Number of pages

19

Pages from-to

1447-1465

UT code for WoS article

000479470500001

EID of the result in the Scopus database

2-s2.0-85070291570