Multivariate joint models for the dynamic prediction of psychosis in individuals with clinical high risk

Dynamic prediction systems of transition to psychosis using joint modelling: extensions to the base system

(2019) Hok Pan Yuen et al.   SCHIZOPHRENIA RESEARCH

Prediction of psychosis in prodrome: development and validation of a simple, personalized risk calculator

(2018) TianHong Zhang et al.   PSYCHOLOGICAL MEDICINE

A new method for analysing transition to psychosis: Joint modelling of time-to-event outcome with time-dependent predictors

(2017) Hok Pan Yuen et al.   INTERNATIONAL JOURNAL OF METHODS IN PSYCHIATRIC RESEARCH

A Severity-Based Clinical Staging Model for the Psychosis Prodrome: Longitudinal Findings From the New York Recognition and Prevention Program

(2017) Ricardo E. Carrión et al.   SCHIZOPHRENIA BULLETIN

Using clinical information to make individualized prognostic predictions in people at ultra high risk for psychosis

(2017) Andrea Mechelli et al.   SCHIZOPHRENIA RESEARCH

Moving From Static to Dynamic Models of the Onset of Mental Disorder

(2017) Barnaby Nelson et al.   JAMA Psychiatry

A comparison of conversion rates, clinical profiles and predictors of outcomes in two independent samples of individuals at clinical high risk for psychosis in China

(2017) Huijun Li et al.   SCHIZOPHRENIA RESEARCH

An Individualized Risk Calculator for Research in Prodromal Psychosis

(2016) Tyrone D. Cannon et al.   AMERICAN JOURNAL OF PSYCHIATRY

Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues

(2016) Graeme L. Hickey et al.   BMC Medical Research Methodology

TheRPackageJMbayesfor Fitting Joint Models for Longitudinal and Time-to-Event Data Using MCMC

(2016) Dimitris Rizopoulos   Journal of Statistical Software

Two-year follow-up of a Chinese sample at clinical high risk for psychosis: timeline of symptoms, help-seeking and conversion

(2016) T. H. Zhang et al.   Epidemiology and Psychiatric Sciences

Performance of joint modelling of time-to-event data with time-dependent predictors: an assessment based on transition to psychosis data

(2016) Hok Pan Yuen et al.   PeerJ

Speed of Psychosis Progression in People at Ultra-High Clinical Risk

(2015) Matthew J. Kempton et al.   JAMA Psychiatry

Prodromal psychosis detection in a counseling center population in China: An epidemiological and clinical study

(2014) TianHong Zhang et al.   SCHIZOPHRENIA RESEARCH

Tools & Techniques - Statistics: Dealing with time-varying covariates in survival analysis – joint models versus Cox models

(2014) Dimitris Rizopoulos et al.   EuroIntervention

The Dynamics of Subthreshold Psychopathology: Implications for Diagnosis and Treatment

(2013) Jim van Os   AMERICAN JOURNAL OF PSYCHIATRY

Long-term Follow-up of a Group at Ultra High Risk (“Prodromal”) for Psychosis

(2013) Barnaby Nelson et al.   JAMA Psychiatry

Predicting Psychosis

(2012) Paolo Fusar-Poli   ARCHIVES OF GENERAL PSYCHIATRY

The Psychosis High-Risk State

(2012) Paolo Fusar-Poli et al.   JAMA Psychiatry

Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data

(2011) Dimitris Rizopoulos   BIOMETRICS

A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes and a time-to-event

(2011) Dimitris Rizopoulos et al.   STATISTICS IN MEDICINE

Global Assessment of Functioning (GAF): properties and frontier of current knowledge

(2010) I. H. Monrad Aas   Annals of General Psychiatry

Prediction of Psychosis in Youth at High Clinical Risk

(2008) Tyrone D. Cannon et al.   ARCHIVES OF GENERAL PSYCHIATRY

A self-reported instrument for prodromal symptoms of psychosis: Testing the clinical validity of the PRIME Screen—Revised (PS-R) in a Japanese population

(2008) H KOBAYASHI et al.   SCHIZOPHRENIA RESEARCH