Gutenberg Open Science: Simulating recurrent event data with hazard functions defined on a total time scale

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DC Element	Wert	Sprache
dc.contributor.author	Jahn, Antje	-
dc.contributor.author	Ingel, Katharina	-
dc.contributor.author	Ozga, Ann-Kathrin	-
dc.contributor.author	Preussler, Stella	-
dc.contributor.author	Binder, Harald	-
dc.date.accessioned	2022-10-06T07:44:47Z	-
dc.date.available	2022-10-06T07:44:47Z	-
dc.date.issued	2015
dc.identifier.uri	https://openscience.ub.uni-mainz.de/handle/20.500.12030/7897	-
dc.description.abstract	Background In medical studies with recurrent event data a total time scale perspective is often needed to adequately reflect disease mechanisms. This means that the hazard process is defined on the time since some starting point, e.g. the beginning of some disease, in contrast to a gap time scale where the hazard process restarts after each event. While techniques such as the Andersen-Gill model have been developed for analyzing data from a total time perspective, techniques for the simulation of such data, e.g. for sample size planning, have not been investigated so far. Methods We have derived a simulation algorithm covering the Andersen-Gill model that can be used for sample size planning in clinical trials as well as the investigation of modeling techniques. Specifically, we allow for fixed and/or random covariates and an arbitrary hazard function defined on a total time scale. Furthermore we take into account that individuals may be temporarily insusceptible to a recurrent incidence of the event. The methods are based on conditional distributions of the inter-event times conditional on the total time of the preceeding event or study start. Closed form solutions are provided for common distributions. The derived methods have been implemented in a readily accessible R script. Results The proposed techniques are illustrated by planning the sample size for a clinical trial with complex recurrent event data. The required sample size is shown to be affected not only by censoring and intra-patient correlation, but also by the presence of risk-free intervals. This demonstrates the need for a simulation algorithm that particularly allows for complex study designs where no analytical sample size formulas might exist. Conclusions The derived simulation algorithm is seen to be useful for the simulation of recurrent event data that follow an Andersen-Gill model. Next to the use of a total time scale, it allows for intra-patient correlation and risk-free intervals as are often observed in clinical trial data. Its application therefore allows the simulation of data that closely resemble real settings and thus can improve the use of simulation studies for designing and analysing studies.	en_GB
dc.description.sponsorship	DFG, Open Access-Publizieren Universität Mainz / Universitätsmedizin	de
dc.language.iso	eng	de
dc.rights	CC BY	*
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	610 Medizin	de_DE
dc.subject.ddc	610 Medical sciences	en_GB
dc.title	Simulating recurrent event data with hazard functions defined on a total time scale	en_GB
dc.type	Zeitschriftenaufsatz	de
dc.identifier.doi	http://doi.org/10.25358/openscience-7882	-
jgu.type.dinitype	article	en_GB
jgu.type.version	Published version	de
jgu.type.resource	Text	de
jgu.organisation.department	FB 04 Medizin	de
jgu.organisation.number	2700	-
jgu.organisation.name	Johannes Gutenberg-Universität Mainz	-
jgu.rights.accessrights	openAccess	-
jgu.journal.title	BMC medical research methodology	de
jgu.journal.volume	15	de
jgu.pages.alternative	Art. 16	de
jgu.publisher.year	2015	-
jgu.publisher.name	BioMed Central	de
jgu.publisher.place	London	de
jgu.publisher.uri	http://dx.doi.org/10.1186/s12874-015-0005-2	de
jgu.publisher.issn	1471-2288	de
jgu.notes.public	Jahn, Antje veröffentlicht auch unter: Jahn-Eimermacher, Antje	de
jgu.organisation.place	Mainz	-
jgu.subject.ddccode	610	de
opus.date.modified	2017-04-25T13:33:44Z
opus.subject.dfgcode	04-205
opus.organisation.string	FB 04: Medizin: Institut für Med. Biometrie, Epidemologie und Informatik	de_DE
opus.identifier.opusid	50723
opus.institute.number	0424
opus.metadataonly	false
opus.type.contenttype	Keine	de_DE
opus.type.contenttype	None	en_EN
opus.affiliated	Jahn, Antje
opus.affiliated	Ingel, Katharina
opus.affiliated	Binder, Harald
jgu.publisher.doi	10.1186/s12874-015-0005-2	de
jgu.organisation.ror	https://ror.org/023b0x485	-
Enthalten in den Sammlungen:	DFG-OA-Publizieren (2012 - 2017)

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