Complete hazard ranking to analyze right-censored data: An ALS survival study

What is survival analysis, and when should I use it?

(2016) Juliana Carvalho Ferreira et al.   Jornal Brasileiro de Pneumologia

Population-Based Evidence that Survival in Amyotrophic Lateral Sclerosis Is Related to Weight Loss at Diagnosis

(2016) Benoît Marin et al.   Neurodegenerative Diseases

Methodological challenges and analytic opportunities for modeling and interpreting Big Healthcare Data

(2016) Ivo D. Dinov   GigaScience

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science

(2016) Julio Montes-Torres et al.   PLoS One

Prognostic Role of Serum Levels of Uric Acid in Amyotrophic Lateral Sclerosis

(2015) Seong-il Oh et al.   Journal of Clinical Neurology

Modeling the course of amyotrophic lateral sclerosis

(2015) Christina Fournier et al.   NATURE BIOTECHNOLOGY

Association between nutritional status and disease severity using the amyotrophic lateral sclerosis (ALS) functional rating scale in ALS patients

(2015) Yongsoon Park et al.   NUTRITION

Regularization Paths for Generalized Linear Models via Coordinate Descent

(2015) Jerome Friedman et al.   Journal of Statistical Software

Evaluating Random Forests for Survival Analysis Using Prediction Error Curves

(2015) Ulla B. Mogensen et al.   Journal of Statistical Software

The phenotypic variability of amyotrophic lateral sclerosis

(2014) Bart Swinnen et al.   Nature Reviews Neurology

The PRO-ACT database: Design, initial analyses, and predictive features

(2014) N. Atassi et al.   NEUROLOGY

Age at onset of amyotrophic lateral sclerosis in China

(2013) M. S. Liu et al.   ACTA NEUROLOGICA SCANDINAVICA

Testing the proportional hazards assumption in case-cohort analysis

(2013) Xiaonan Xue et al.   BMC Medical Research Methodology

A Flexible Alternative to the Cox Proportional Hazards Model for Assessing the Prognostic Accuracy of Hospice Patient Survival

(2012) Branko Miladinovic et al.   PLoS One

Comparison of procedures to assess non-linear and time-varying effects in multivariable models for survival data

(2011) Anika Buchholz et al.   BIOMETRICAL JOURNAL

Accelerated clinical discovery using self-reported patient data collected online and a patient-matching algorithm

(2011) Paul Wicks et al.   NATURE BIOTECHNOLOGY

Variables with time-varying effects and the Cox model: Some statistical concepts illustrated with a prognostic factor study in breast cancer

(2010) Carine A Bellera et al.   BMC Medical Research Methodology

Comparing measures of model selection for penalized splines in Cox models

(2009) Elizabeth J. Malloy et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Estimating classification error rate: Repeated cross-validation, repeated hold-out and bootstrap

(2009) Ji-Hyun Kim   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Study of 962 patients indicates progressive muscular atrophy is a form of ALS

(2009) W. -K. Kim et al.   NEUROLOGY

Random survival forests

(2008) Hemant Ishwaran et al.   Annals of Applied Statistics

Accelerated failure time models provide a useful statistical framework for aging research

(2008) William R. Swindell   EXPERIMENTAL GERONTOLOGY