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Cremaschi A, De Iorio M, Seng Chong Y, Broekman B, Meaney MJ, Kee MZL. A Bayesian nonparametric approach to dynamic item-response modeling: An application to the GUSTO cohort study. Stat Med 2021; 40:6021-6037. [PMID: 34412151 PMCID: PMC9546363 DOI: 10.1002/sim.9167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 08/03/2021] [Accepted: 08/03/2021] [Indexed: 11/08/2022]
Abstract
Statistical analysis of questionnaire data is often performed employing techniques from item-response theory. In this framework, it is possible to differentiate respondent profiles and characterize the questions (items) included in the questionnaire via interpretable parameters. These models are often crosssectional and aim at evaluating the performance of the respondents. The motivating application of this work is the analysis of psychometric questionnaires taken by a group of mothers at different time points and by their children at one later time point. The data are available through the GUSTO cohort study. To this end, we propose a Bayesian semiparametric model and extend the current literature by: (i) introducing temporal dependence among questionnaires taken at different time points; (ii) jointly modeling the responses to questionnaires taken from different, but related, groups of subjects (in our case mothers and children), introducing a further dependency structure and therefore sharing of information; (iii) allowing clustering of subjects based on their latent response profile. The proposed model is able to identify three main groups of mother/child pairs characterized by their response profiles. Furthermore, we report an interesting maternal reporting bias effect strongly affecting the clustering structure of the mother/child dyads.
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Affiliation(s)
- Andrea Cremaschi
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Brenner Centre for Molecular Medicine, Singapore
| | - Maria De Iorio
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Brenner Centre for Molecular Medicine, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Division of Science, Yale-NUS College, Singapore, Singapore.,Department of Statistical Science, University College London, London, UK
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Brenner Centre for Molecular Medicine, Singapore.,Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Birit Broekman
- Department of Psychiatry, VU Medical Centre, Amsterdam, the Netherlands
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Brenner Centre for Molecular Medicine, Singapore.,Department of Psychiatry, Douglas Mental Health University Research Institute, McGill University, Montreal, Quebec, Canada
| | - Michelle Z L Kee
- Singapore Institute for Clinical Sciences (SICS), Agency for Science, Technology and Research (A*STAR), Brenner Centre for Molecular Medicine, Singapore
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Takahashi F, Sato H. Editorial: Adolescence Revisited: New Frontier in Psychological Research. JAPANESE PSYCHOLOGICAL RESEARCH 2020. [DOI: 10.1111/jpr.12283] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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