scholarly journals Raking and regression calibration: Methods to address bias from correlated covariate and time‐to‐event error

2020 ◽  
Vol 40 (3) ◽  
pp. 631-649
Author(s):  
Eric J. Oh ◽  
Bryan E. Shepherd ◽  
Thomas Lumley ◽  
Pamela A. Shaw
Keyword(s):  
Regression Calibration ◽  
Time To Event ◽  
Calibration Methods

Equivalence of regression calibration methods in main study/external validation study designs

2003 ◽  
Vol 113 (2) ◽  
pp. 527-539 ◽  
Author(s):  
Sally W. Thurston ◽  
Donna Spiegelman ◽  
David Ruppert
Keyword(s):  
Validation Study ◽  
External Validation ◽  
Regression Calibration ◽  
Main Study ◽  
Calibration Methods ◽  
External Validation Study ◽  
Study Designs

Research on Univariate and Multiple Linear Regression Calibration Methods by Laser Induced Breakdown Spectroscopy

2015 ◽  
Vol 52 (9) ◽  
pp. 093001
Author(s):  
余洋 Yu Yang ◽  
赵南京 Zhao Nanjing ◽  
王寅 Wang Yin ◽  
方丽 Fang Li ◽  
孟德硕 Meng Deshuo ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Laser Induced Breakdown Spectroscopy ◽  
Regression Calibration ◽  
Breakdown Spectroscopy ◽  
Calibration Methods ◽  
Laser Induced Breakdown

Intensity and direction dimensions of competitive state anxiety: Relationship to performance through the time-to-event paradigm

2003 ◽  
Author(s):  
Nektarios A. Stavrou ◽  
Maria Psychountaki ◽  
Yannis Zervas
Keyword(s):  
State Anxiety ◽  
Time To Event

Bayesian Frailty Model for Time to Event Breast Cancer Data

2011 ◽  
Vol 4 (2) ◽  
pp. 8-12
Author(s):  
Leo Alexander T Leo Alexander T ◽  
◽  
Pari Dayal L Pari Dayal L ◽  
Valarmathi S Valarmathi S ◽  
Ponnuraja C Ponnuraja C ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Frailty Model ◽  
Breast Cancer Data ◽  
Time To Event ◽  
Cancer Data

INTENSITY AND DIRECTION DIMENSIONS OF COMPETITIVE STATE ANXIETY: A TIME-TO-EVENT APPROACH

2006 ◽  
Vol 103 (5) ◽  
pp. 91 ◽  
Author(s):  
NEKTARIOS A. STAVROU
Keyword(s):  
State Anxiety ◽  
Time To Event

Development and validation of risk stratification models for adult spinal deformity surgery

2019 ◽  
Vol 31 (4) ◽  
pp. 587-599 ◽  
Author(s):  
Ferran Pellisé ◽  
Miquel Serra-Burriel ◽  
Justin S. Smith ◽  
Sleiman Haddad ◽  
Michael P. Kelly ◽  
...  
Keyword(s):  
Spinal Deformity ◽  
Adult Spinal Deformity ◽  
The United States ◽  
Adverse Outcomes ◽  
High Rate ◽  
Prognostic Models ◽  
Time To Event ◽  
European Continent ◽  
Event Risk ◽  
Risk Estimates

OBJECTIVEAdult spinal deformity (ASD) surgery has a high rate of major complications (MCs). Public information about adverse outcomes is currently limited to registry average estimates. The object of this study was to assess the incidence of adverse events after ASD surgery, and to develop and validate a prognostic tool for the time-to-event risk of MC, hospital readmission (RA), and unplanned reoperation (RO).METHODSTwo models per outcome, created with a random survival forest algorithm, were trained in an 80% random split and tested in the remaining 20%. Two independent prospective multicenter ASD databases, originating from the European continent and the United States, were queried, merged, and analyzed. ASD patients surgically treated by 57 surgeons at 23 sites in 5 countries in the period from 2008 to 2016 were included in the analysis.RESULTSThe final sample consisted of 1612 ASD patients: mean (standard deviation) age 56.7 (17.4) years, 76.6% women, 10.4 (4.3) fused vertebral levels, 55.1% of patients with pelvic fixation, 2047.9 observation-years. Kaplan-Meier estimates showed that 12.1% of patients had at least one MC at 10 days after surgery; 21.5%, at 90 days; and 36%, at 2 years. Discrimination, measured as the concordance statistic, was up to 71.7% (95% CI 68%–75%) in the development sample for the postoperative complications model. Surgical invasiveness, age, magnitude of deformity, and frailty were the strongest predictors of MCs. Individual cumulative risk estimates at 2 years ranged from 3.9% to 74.1% for MCs, from 3.17% to 44.2% for RAs, and from 2.67% to 51.9% for ROs.CONCLUSIONSThe creation of accurate prognostic models for the occurrence and timing of MCs, RAs, and ROs following ASD surgery is possible. The presented variability in patient risk profiles alongside the discrimination and calibration of the models highlights the potential benefits of obtaining time-to-event risk estimates for patients and clinicians.

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