Skip to Main content Skip to Navigation
Journal articles

A hypothesis testing procedure for random changepoint mixed models

Abstract : In biomedical research, random changepoint mixed models are used to take into account an individual breakpoint in a biomarker trajectory. This may be observed in the cognitive decline measured by psychometric tests in the prediagnosis phase of Alzheimer's disease. The existence, intensity and duration of this accelerated decline can depend on individual characteristics. The main objective of our work is to propose inferential methods to assess the existence of this phase of accelerated decline, ie, the existence of a random changepoint. To do so, we use a mixed model with two linear phases and test the nullity of the parameter measuring the difference of slopes between the two phases. Because we face the issue of nuisance parameters being unidentifiable under the null hypothesis, the supremum of the classic score test statistic on these parameters is used. The asymptotic distribution of the supremum under the null is approached with a perturbation method based on the multiplier bootstrap. The performance of our testing procedure is assessed via simulations and the test is applied to the French cohort PAQUID of elderly subjects to study the shape of the prediagnosis decline according to educational level. The test is significant for both educational levels and the estimated trajectories confirmed that educational level is a good marker for cognitive reserve.
Keywords : Biostatistics SEPIA
Document type :
Journal articles
Complete list of metadata
Contributor : Oskar Admin Connect in order to contact the contributor
Submitted on : Wednesday, March 10, 2021 - 9:15:29 AM
Last modification on : Wednesday, February 16, 2022 - 12:22:02 PM




Corentin Segalas, Helene Amieva, Helene Jacqmin-Gadda. A hypothesis testing procedure for random changepoint mixed models. Statistics in Medicine, Wiley-Blackwell, 2019, 38 (20), pp.3791-3803. ⟨10.1002/sim.8195⟩. ⟨hal-03164561⟩



Record views