EconPapers    
Economics at your fingertips  
 

Testing for the Functional Form of a Continuous Covariate in the Shared-Parameter Joint Model

Xavier Piulachs, Anouar El Ghouch and Ingrid Van Keilegom
Additional contact information
Xavier Piulachs: Polytechnic Universityof Catalonia
Anouar El Ghouch: Université catholique de Louvain, LIDAM/ISBA, Belgium
Ingrid Van Keilegom: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2025026, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: Shared-parameter joint modeling is a useful technique for properly associating longitudinal and time-to-event data. When the interest is in the survival outcome, the conditional logarithm of the hazard function for an event is conventionally presumed to be linearly related over time to a set of explanatory covariates, among other terms. However, this hypothesis is quite restrictive and may yield misleading results. Our objective here is to easily check such a modeling assumption for any continuous fixed covariate. For this purpose, we examine the appropriateness of a nonparametric test criterion based on a penalty-modified version of the Akaike information criterion. An extensive numerical study is conducted to check the validity of the test within the joint modeling framework, while determining the extent to which the function embedding the continuous covariate deviates from linearity. Furthermore, once a deviation from linearity is detected, the improvement in the model's predictive performance is examined. The usefulness of the testing procedure is illustrated using a clinical trial with HIV-infected subjects. Specifically, our example focuses on properly accounting for the effect of nadir CD4 cell count within a predictive joint model for the time to immune recovery.

Keywords: Akaike information criterion; order selection test; nonlinear covariate; joint model (search for similar items in EconPapers)
Pages: 16
Date: 2026-01-01
Note: In: Statistics in Medicine, 2025, vol. 44(5), e10340
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2025026

DOI: 10.1002/sim.10340

Access Statistics for this paper

More papers in LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA) Voie du Roman Pays 20, 1348 Louvain-la-Neuve (Belgium). Contact information at EDIRC.
Bibliographic data for series maintained by Nadja Peiffer ().

 
Page updated 2026-02-05
Handle: RePEc:aiz:louvar:2025026