The University of Southampton
University of Southampton Institutional Repository

Flexible parametric illness-death models

Flexible parametric illness-death models
Flexible parametric illness-death models

It is usual in time-to-event data to have more than one event of interest, for example, time to death from different causes. Competing risks models can be applied in these situations where events are considered mutually exclusive absorbing states. That is, we have some initial state-for example, alive with a diagnosis of cancer-and we are interested in several different endpoints, all of which are final. However, the progression of disease will usually consist of one or more intermediary events that may alter the progression to an endpoint. These events are neither initial states nor absorbing states. Here we consider one of the simplest multistate models, the illness-death model. stpm2illd is a postestimation command used after fitting a flexible parametric survival model with stpm2 to estimate the probability of being in each of four states as a function of time. There is also the option to generate confidence intervals and transition hazard functions. The new command is illustrated through a simple example.

Flexible parametric models, Illdprep, Multistate models, St0316, Stpm2illd, Survival analysis
1536-867X
759-775
Hinchliffe, Sally R.
9e451f5f-fc5e-415c-8adf-f972cb7ce5f9
Scott, David A.
19b5fd34-9974-4ae4-8be0-27a693639e20
Lambert, Paul C.
9538e2f6-64da-41a6-a8f7-7f3199596035
Hinchliffe, Sally R.
9e451f5f-fc5e-415c-8adf-f972cb7ce5f9
Scott, David A.
19b5fd34-9974-4ae4-8be0-27a693639e20
Lambert, Paul C.
9538e2f6-64da-41a6-a8f7-7f3199596035

Hinchliffe, Sally R., Scott, David A. and Lambert, Paul C. (2013) Flexible parametric illness-death models. The Stata Journal, 13 (4), 759-775. (doi:10.1177/1536867X1301300405).

Record type: Article

Abstract

It is usual in time-to-event data to have more than one event of interest, for example, time to death from different causes. Competing risks models can be applied in these situations where events are considered mutually exclusive absorbing states. That is, we have some initial state-for example, alive with a diagnosis of cancer-and we are interested in several different endpoints, all of which are final. However, the progression of disease will usually consist of one or more intermediary events that may alter the progression to an endpoint. These events are neither initial states nor absorbing states. Here we consider one of the simplest multistate models, the illness-death model. stpm2illd is a postestimation command used after fitting a flexible parametric survival model with stpm2 to estimate the probability of being in each of four states as a function of time. There is also the option to generate confidence intervals and transition hazard functions. The new command is illustrated through a simple example.

This record has no associated files available for download.

More information

Published date: 30 December 2013
Keywords: Flexible parametric models, Illdprep, Multistate models, St0316, Stpm2illd, Survival analysis

Identifiers

Local EPrints ID: 441442
URI: http://eprints.soton.ac.uk/id/eprint/441442
ISSN: 1536-867X
PURE UUID: b36dbfdd-f862-4e01-933d-c8c392b3c84d
ORCID for David A. Scott: ORCID iD orcid.org/0000-0001-6475-8046

Catalogue record

Date deposited: 12 Jun 2020 16:30
Last modified: 17 Mar 2024 04:02

Export record

Altmetrics

Contributors

Author: Sally R. Hinchliffe
Author: David A. Scott ORCID iD
Author: Paul C. Lambert

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×