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Semiparametric additive marginal regression models for multiple type recurrent events

Xiaolin Chen, Qihua Wang, Jianwen Cai, Viswanathan Shankar
2012 Lifetime Data Analysis  
In many studies, there are more than one type of events of interest. Cai and Schaubel (2004) advocated a proportional marginal rate model for multiple type recurrent event data.  ...  In this paper, we propose a general additive marginal rate regression model. Estimating equations approach is used to obtain the estimators of regression coefficients and baseline rate function.  ...  John and the Department of Nephrology, Christian Medical College, Vellore India for providing renal transplant data used in this investigation.  ... 
doi:10.1007/s10985-012-9226-4 pmid:22899088 pmcid:PMC3844629 fatcat:hmh3jgbzzvdp7acydyeutvfb4y

Dynamic Prediction for Multiple Repeated Measures and Event Time Data: An Application to Parkinson's Disease [article]

Jue Wang, Sheng Luo, Liang Li
2017 arXiv   pre-print
In this article, we first propose a joint model that consists of a semiparametric multilevel latent trait model (MLLTM) for the multiple longitudinal outcomes, and a survival model for event time.  ...  We develop a Bayesian approach for parameter estimation and a dynamic prediction framework for predicting target patients' future outcome trajectories and risk of a survival event, based on their multivariate  ...  The authors acknowledge the Texas Advanced Computing Center (TACC) for providing high-performing computing resources.  ... 
arXiv:1603.06476v2 fatcat:cwineh75pves3g3mz74ie5oxny

Estimating Cure Rates From Survival Data

A. D Tsodikov, J. G Ibrahim, A. Y Yakovlev
2003 Journal of the American Statistical Association  
2) In some settings the model can be interpreted in terms of biologically meaningful parameters. (3) The model structure is particularly suitable for semiparametric and Bayesian methods of statistical  ...  This approach has the following distinct advantages: (1) It allows for a natural way to extend the proportional hazards regression model, leading to a wide class of extended hazard regression models. (  ...  Acknowledgments The authors wish to thank the editor, the associate editor, and three referees for several suggestions and editorial changes which have greatly improved the paper. The research of A.  ... 
doi:10.1198/01622145030000001007 pmid:21151838 pmcid:PMC2998771 fatcat:3byf6lcynjhnndmvu6hgo6wyxi

Bayesian analysis of multi-type recurrent events and dependent termination with nonparametric covariate functions

Li-An Lin, Sheng Luo, Bingshu E Chen, Barry R Davis
2015 Statistical Methods in Medical Research  
We simultaneous model the multi-type recurrent events and a dependent terminal event, both with non-parametric covariate functions.  ...  In this paper, we develop a Bayesian inference for multivariate frailty model to account for dependent termination as well as the correlation among event types.  ...  Cai and Schaubel 10 proposed a class of semiparametric marginal mean/rates models for the multi-type recurrent events data with a general relative risk form and established a partial likelihood score function  ... 
doi:10.1177/0962280215613378 pmid:26546256 pmcid:PMC5061632 fatcat:5yiyoandu5f2zds2otmrludo4m

The Epidemiology of Recurrent Violence and Its Relationship with Sentence Time in the Romanian Juvenile Prison System: A Two-Year Cohort Study

Carmen-Valeria Baias
2022 Open Journal of Epidemiology  
Research suggests that a small number of persistent violent offenders are responsible for a majority of prison violence and tend to behave violently to a disproportionate amount.  ...  associated with violence.  ...  Dorin Muresan, for their practical support and understanding over the course of this study. C.-V. Baias  ... 
doi:10.4236/ojepi.2022.121002 fatcat:ucm6li37end4ji5l6zdugxzjf4

Smoothing Spline ANOVA Frailty Model for Recurrent Event Data

Pang Du, Yihua Jiang, Yuedong Wang
2011 Biometrics  
Gap time hazard estimation is of particular interest in recurrent event data. This article proposes a fully nonparametric approach for estimating the gap time hazard.  ...  Smoothing spline analysis of variance (ANOVA) decompositions are used to model the log gap time hazard as a joint function of gap time and covariates, and general frailty is introduced to account for between-subject  ...  Acknowledgements The authors thank the editor, the associate editor, and two referees for their insightful comments that have helped improve the article.  ... 
doi:10.1111/j.1541-0420.2011.01584.x pmid:21457192 fatcat:i6paq2lqknafdo2rzfs2m2sm4a

A bivariate joint frailty model with mixture framework for survival analysis of recurrent events with dependent censoring and cure fraction

Richard Tawiah, Geoffrey J. McLachlan, Shu Kay Ng
2019 Biometrics  
The latency part of the model consists of two intensity functions for the hazard rates of recurrent events and death, wherein a bivariate frailty is introduced by means of the generalized linear mixed  ...  A bivariate joint frailty mixture cure model is proposed to allow for dependent censoring and cure fraction in recurrent event data.  ...  Acknowledgements The authors are grateful to the reviewers and an associate editor for their helpful comments.  ... 
doi:10.1111/biom.13202 pmid:31863594 fatcat:a7lf6z5w5ra5jluvvt3z57wjlq

Predicting recurrence of depression

P. Kurdyak, J. Cairney
2011 CMAJ - Canadian Medical Association Journal  
We included demographic, mental and physical health factors as predictors in the multivariable regression model to compare people with different trajectories.  ...  Our aim was to identify factors associated with a long-term negative prognosis of depression.  ...  Irene Wong, Statistics Canada, for her assistance with data access and use. The research and analysis are based on data from Statistics Canada.  ... 
doi:10.1503/cmaj.111664 pmid:22025651 pmcid:PMC3225413 fatcat:xnm77lpz2ffabivbjqfifselnq

Dynamic Analysis of Recurrent Event Data with Missing Observations, with Application to Infant Diarrhoea in Brazil

2007 Scandinavian Journal of Statistics  
We discuss modelling strategies and show the advantages of taking an event history approach with an additive discrete time regression model.  ...  This paper examines and applies methods for modelling of longitudinal binary data subject to both intermittent missingness and dropout.  ...  The work of Ørnulf Borgan was done partly during a sabbatical leave at the School of Mathematics and Statistics, University of Newcastle upon Tyne, UK, in the spring of 2005, and partly during a research  ... 
doi:10.1111/j.1467-9469.2006.00525.x fatcat:2plly7wqc5ewxm2rn5zlkkr6f4

Regression models for infant mortality data in Norwegian siblings, using a compound Poisson frailty distribution with random scale

T. A. Moger, O. O. Aalen
2008 Biostatistics  
When combined with a parametric baseline hazard, this yields a model with heterogeneity on both the individual and the family level and a subgroup with zero frailty, corresponding to people not experiencing  ...  the event.  ...  ACKNOWLEDGMENTS We are grateful to the Medical Birth Registry of Norway and Rolv Terje Lie for giving us access to their data.  ... 
doi:10.1093/biostatistics/kxn003 pmid:18304994 fatcat:ujp4nt44grhbxorilrnjsima4i

Interval censoring

Zhigang Zhang, Jianguo Sun
2009 Statistical Methods in Medical Research  
Acknowledgments The authors wish to thank Professor Per Kragh Andersen and a reviewer for their helpful comments. References  ...  For applications in survival analysis, the random variable is the time to some event such as death, a disease recurrence or a distant metastasis.  ...  In addition to the models discussed above, another attractive semiparametric regression model is the additive hazards model given by (7) with respect to the hazard function of T given Z = z.  ... 
doi:10.1177/0962280209105023 pmid:19654168 pmcid:PMC3684949 fatcat:vlezhkc3wrbdlgoi2752y6thku

Comparison of Time-to-First-Event and Recurrent Event Methods in Multiple Sclerosis Trials [article]

Alexandra Būhler
2021 arXiv   pre-print
models) are presented to demonstrate challenges in defining disability progression and to identify analysis methods suitable for treatment comparisons in MS trials with disability progression endpoints  ...  Data on disease activity and results from two simulation studies which compare analyses of the time to the first event with recurrent event analyses (including negative binomial, Andersen-Gill and Lin-Wei-Ying-Yang  ...  His research enthusiasm for complex event history analysis has strongly influenced my interests in a positive sense.  ... 
arXiv:2111.01937v1 fatcat:ykg25uudnfditcft6fubdgbwxe

Altona Prognostic Index: A New Prognostic Index for ER-Positive and Her2-Negative Breast Cancer of No Special Type

Anne-Sophie Wegscheider, Bernhard Ulm, Kay Friedrichs, Christoph Lindner Lindner, Axel Niendorf
2021 Cancers  
Furthermore, it was intended to develop an even superior risk stratification model considering an additional variable, namely the patient's age at the time of diagnosis.  ...  The aim of the present study was to demonstrate the validity of the long-known Nottingham prognostic index (NPI) in a large retrospective study (n = 6654 women with a first primary unilateral and unifocal  ...  Acknowledgments: We most sincerely thank Peter Fritz, Dimitrij Tschodu, Kurt Ulm and Christoph Wagener for the critical discussion of the manuscript.  ... 
doi:10.3390/cancers13153799 fatcat:ybu676knw5hjfjfqagczuxbhiu

Constructing Multivariate Survival Trees: The MST Package for R

Peter Calhoun, Xiaogang Su, Martha Nunn, Juanjuan Fan
2018 Journal of Statistical Software  
Trees can handle a large number of predictors with mixed types and do not require predictor variable transformation or selection.  ...  The package can also simulate high-dimensional, multivariate survival data from marginal and frailty models.  ...  Nici Kimmes, DDS for her help in extracting the data from AxiUm.  ... 
doi:10.18637/jss.v083.i12 fatcat:5w3zy5us5va5liwsf4wddydcmu

In-depth mining of clinical data: the construction of clinical prediction model with R

Zhi-Rui Zhou, Wei-Wei Wang, Yan Li, Kai-Rui Jin, Xuan-Yi Wang, Zi-Wei Wang, Yi-Shan Chen, Shao-Jia Wang, Jing Hu, Hui-Na Zhang, Po Huang, Guo-Zhen Zhao (+3 others)
2019 Annals of Translational Medicine  
The thirteenth section mainly introduces how to deal with the survival data outcome using competitive risk model with R.  ...  The fourteenth section mainly introduces how to draw the nomogram of the competitive risk model with R.  ...  Competitive risk model (multivariate analysis) The following is a multivariate analysis of survival data considering competitive risk events.  ... 
doi:10.21037/atm.2019.08.63 pmid:32042812 pmcid:PMC6989986 fatcat:3kskwtfz65eapa726vxivmyctq
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