Abstract
Psychotic disorder is a group of serious illness that
affects the mind. The symptoms are severe and it affects over 5% of
the population. Among illness that affect people aged in 15 to 44,
schizophrenia is the 8th leading cause of the disability
worldwide. The first aim of this analysis is to
conduct a latent class analysis on the clinical
characteristics of adolescents at high risk of psychosis using the
software Latent Gold. The second aim is to
model the time to onset of psychosis in high-risk
youth based on latent classes of comprehensive clinical information
and socio-demographic variables. In this analysis, we
used the Latent Class Analysis (LCA) approach to analyze variables
collected as the North American Prodrome Longitudinal Study
(NAPLS). The results showed that the four-class model was preferred
according to the model selection criteria, such as AIC, BIC, and
ICL-BIC. Based on these four subgroups, a proportional hazards
model was used to characterize the relationship. In comparing
the proportional hazards regression models with and
without covariate measurement error, we found that the standard
errors of the coefficients in the model with measurement error are
smaller than the ones without measurement error.
Table of Contents
Contents
1. Introduction 1
2. Method 6
2.1 Coding Psychosis 6
2.2 Latent Class Analysis 7
2.2.1 Basic components of a Latent Class Cluster model 7
2.2.2 Probability Structure 8
2.2.3 Conditional distributions 9
2.2.4 Latent variable 10
2.2.5 Local independence 11
2.3 Proportional hazards model 12
2.4 Measurement with error 14
3. Results 17
4. Discussion 21
4.1 Discussion of results 21
4.2 Future work 21
5. Reference 24
6. Appendices 28
Appendix 1 28
Appendix 2 29
About this Master's Thesis
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