Journal article
Adjusting a subject-specific time of event in longitudinal studies
Statistical methods in medical research, Vol.29(7), pp.1787-1798
07/2020
DOI: 10.1177/0962280219876957
PMID: 31549571
Abstract
Biomedical studies often involve an event that occurs to individuals at different times and has a significant influence on individual trajectories of response variables over time. We propose a statistical model to capture the mean trajectory alteration caused by not only the occurrence of the event but also the subject-specific time of the event. The proposed model provides a post-event mean trajectory smoothly connected with the pre-event mean trajectory by allowing the model parameters associated with the post-event mean trajectory to vary over time of the event. A goodness-of-fit test is considered to investigate how well the proposed model is fit to the data. Hypothesis tests are also developed to assess the influence of the subject-specific time of event on the mean trajectory. Theoretical and simulation studies confirm that the proposed tests choose the correctly specified model consistently and examine the effect of the subject-specific time of event successfully. The proposed model and tests are also illustrated by the analysis of two real-life data from a biomarker study for HIV patients along with their own time of treatment initiation and a body fatness study in girls with different age of menarche.
Details
- Title: Subtitle
- Adjusting a subject-specific time of event in longitudinal studies
- Creators
- Hyunkeun Ryan Cho - Department of Biostatistics, University of Iowa, Iowa City, IA, USASeonjin Kim - Department of Statistics, Miami University, Oxford, OH, USAMyung Hee Lee - Center for Global Health, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Resource Type
- Journal article
- Publication Details
- Statistical methods in medical research, Vol.29(7), pp.1787-1798
- DOI
- 10.1177/0962280219876957
- PMID
- 31549571
- ISSN
- 0962-2802
- eISSN
- 1477-0334
- Language
- English
- Date published
- 07/2020
- Academic Unit
- Biostatistics
- Record Identifier
- 9984214671102771
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