Abstract
The assessment of the lifetime prevalence of mental disorders under comorbidity conditions is an important area in mental health research. Because information on lifetime disorders is usually gathered retrospectively within cross-sectional studies, the information is necessarily right censored and this should be taken into account when setting up models for the estimation of lifetime prevalences. We propose a factor analytic discrete time survival model combining mixture item response theory and discrete time hazard functions to describe disorder associations while accounting for censoring. This model is used for describing the lifetime prevalence and comorbidity of eight depression and anxiety disorders from the European Study of the Epidemiology of Mental Disorders.
Original language | English |
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Pages (from-to) | 85-102 |
Number of pages | 18 |
Journal | Journal of the Royal Statistical Society. Series C: Applied Statistics |
Volume | 63 |
Issue number | 1 |
DOIs | |
Publication status | Published - Jan-2014 |
Externally published | Yes |
Keywords
- Cure fraction
- Disorder diathesis
- Internalizing disorders
- Item response theory
- Latent classes
- Psychiatric comorbidity
- NATIONAL COMORBIDITY SURVEY
- LONG-TERM SURVIVORS
- DSM-IV DISORDERS
- AGE-OF-ONSET
- SURVEY REPLICATION
- ESEMED PROJECT
- JOINT ANALYSIS
- TIME
- PREVALENCE
- EVENT