Single index regression models in the presence of censoring depending on the covariates

Single index regression models in the presence of censoring depending on the covariates
Single index regression models in the presence of censoring depending on the covariates
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LIDA 2017 : Invited and Contributed Sessions

Cox and Fine-Gray regression models yielded similar risk estimates for baseline characteristics, with the exception of diabetes duration, which was significant in the Cox but not Fine-Gray model. wherein the event of interest could potentially occur after censoring. The presence of competing risks complicates the analysis of time to event

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A comparison of the conditional inference survival forest

Title: Single index regression models in the presence of censoring depending on the covariates. Authors: Olivier Lopez, Valentin Patilea, (X',Y)', where X is d-dimensional and Y is one-dimensional. We assume that Y is subject to random right censoring. The aim of this paper is twofold.

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When conducting multiple regression, when should you

Performance of Goodness-of-Fit Tests for the Cox Proportional Hazards Model with Time-Varying Covariates. Shannon Grant, Ying Qing Chen, p index p covariates. Zhou M. Understanding the Cox regression models with time-change covariates. American Statistician.

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[hal-00644892, v1] Single index regression models in the

extent of censoring is likely to vary depending on related quality of life and age in the presence of censoring. Source: adapted from Kennedy (1998, page 250). 912. general Tobit regression estimates of di•erent models can also be quite sensitive tonon-normality

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The Use and Interpretation of Competing Risks Regression

4/15/2012 · Purpose: Competing risks observations, in which patients are subject to a number of potential failure events, are a feature of most clinical cancer studies. With competing risks, several modeling approaches are available to evaluate the relationship of covariates to cause-specific failures. We discuss the use and interpretation of commonly used competing risks regression models.

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Nonparametric Regression with Nonparametrically Generated

Single-index models are natural extensions of linear models and circumvent the so-called curse of dimensionality. Lopez, Olivier, Patilea, Valentin, Lopez

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Performance of Disease Risk Scores, Propensity Scores, and

In the presence of right censoring, a dummy variable is defined that assumes the value 1 if the ith individual’s spell is censored, and 0 otherwise. including left censoring, time-varying covariates, multiple spells, multiple-duration processes, and simultaneous-duration processes. Cox, D.R. (1972). Regression models and life tables

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Publications - Site personnel d'Olivier Lopez - Google Sites

Single index regression models in the presence of censoring depending on the covariates Olivier L opez 1 Valentin P atilea 2 Ingrid V an Keilegom 3 November 25, 2011 Abstract Consider a random vector (X 0;Y )0, where X is d-dimensional and Y is one- dimensional.

Single index regression models in the presence of censoring depending on the covariates
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Learning (predictive) risk scores in the presence of

7/12/2011 · For each simulated sample, the data were fit by using 4 different Poisson regression models. We first fit the exposure and all of the individual covariates in a single regression model, which was designated the “traditional” model.

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Cui , Härdle , Zhu : The EFM approach for single-index models

. Bernoulli, 19, 721-747. Curriculum Vitae Ingrid Van Keilegom, June 2, 2015 9 85.

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AGeneralApproachforCureModels inSurvivalAnalysis - arXiv

7/28/2017 · A comparison of the conditional inference survival forest model to random survival forests based on a simulation study as well as on two applications with time-to-event data the study has shown that there are some variations in predictive performance for these three models in the presence of covariates with many vs those with fewer split

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Inference in generalized linear regression models with a

Regression under Cox’s model for recall-based time-to-event data in observational studies. Author links open overlay panel Sedigheh Mirzaei Salehabadi is widely used in the analysis of event time data with covariates. The method of analysis such as single index regression models (Chaudhuri, 2007) and models with random

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www.ce.utexas.edu

Single index regression models in the presence of censoring depending on the covariates (2011) Cached. Download Links , year = 2011} Share. OpenURL . Abstract.

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Single index regression models in the presence of

“Accelerated Failure Time Models for Semi-Competing Risks Data in the Presence of Complex Censoring” “Quantile regression models for interval-censored failure time data” “Single Index Models in Proportional Hazard Regression for Precision Medicine”

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Consistency of nonlinear regression quantiles under Type I

Single index regression models in the presence of censoring depending on the covariates Olivier Lopez , Valentin Patilea , and Ingrid Van Keilegom More by Olivier Lopez

Single index regression models in the presence of censoring depending on the covariates
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[1111.6232] Single index regression models in the presence

The presence of these features creates special problems in analysing the data and needs to be carefully considered when constructing likelihood functions. by including covariates depending on the history. 12 For the illness Liu L. Polynomial spline estimation and inference of proportional hazards regression models with flexible relative

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Curriculum Vitae - UNC Gillings School of Global Public Health

: Authors: (X',Y)', where X is d-dimensional and Y is one-dimensional. We assume that Y is subject to random right censoring. The aim of this paper is twofold. Second, we assume that the relation between X and Y is given by a mean regression single

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Application of random survival forests in understanding

Rosie Meng Richard Woodman Steven Coles Erin Symonds Email: [email protected] Stata User Group Meeting • Left censoring No difference mathematically Index colonoscopy Onset of risk (t0) X 1st surveillance colonoscopy risks regression models. …

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Marginal Structural Models and Causal Inference in

"Consistency of nonlinear regression quantiles under Type I censoring weak dependence and general covariate design," University of Regensburg Working Papers in Business, Economics and Management Information Systems 406, University of Regensburg, Department of Economics.

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(PDF) Single index regression models in the presence of

Abstract: The article introduces how to validate regression models in the analysis of competing risks. The prediction accuracy of competing risks regression models can be assessed by discrimination and calibration. The area under receiver operating characteristic curve (AUC) or Concordance-index, and calibration plots have been widely used as measures of discrimination and calibration

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Single-index Regression models with right-censored responses

1/11/2018 · The MI based on weighted CQR offers a more valid statistical approach to evaluate a biomarker of disease in the presence of both issues with censoring and missing data in early visits. Then appropriate regression models such as logistic regression model can be used to estimate BMC Medical Research Methodology. ISSN: 1471-2288. Contact us.

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Methodological comparison of marginal structural model

We consider semiparametric analysis of competing risks data subject to mixed case interval censoring. Motivated to automatically partition predictors into a linear part and a nonlinear part in partially linear single-index models (PLSIM), we consider the estimation of a partially linear single-index model where the linear part and the

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A simulation study on estimating biomarker–treatment

Single index regression models in the presence of censoring depending on the covariates. Single index regression models in the presence of. censoring depending on the cov ariates.

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Regression Analysis of Fold-Increase Endpoints Using a

In case you use gradient descent to fit your model, standardizing covariates may speed up convergence (because when you have unscaled covariates, the corresponding parameters may inappropriately dominate the gradient).

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Performance of Goodness-of-Fit Tests for the Cox

Principled approaches to handle interval-censoring at a single time point are widely available (e.g., Helsel 2005 Helsel, D. R. Regression Models and Risk Parameters. Recent research has suggested that a higher body mass index

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Single index regression models in the presence of

O.Lopez, V. Patilea, I. Van Keilegom Single-index regression models in the presence of censoring depending on the covariates, Bernoulli, Volume 19, Number 3, 2013, Pages 721-747 full text A. Oueslati, O. Lopez A proportional hazards regression model with change-points in the baseline function, Lifetime Data Analysis, Volume 18, Issue 1, 2013

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The Fine-Gray model under interval censored competing

9/7/2017 · In the presence of non-proportional hazards covariates, random survival forest models under the two split rules (log-rank and log-rank score, respectively) show a much better predictive performance. Their predictive performance exhibited is better than that of models based strictly on the PH assumption.

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Competing Risk of Death With End-Stage Renal Disease in

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references. Austin and Hoch, 2004. Estimating linear regression models in the presence of a censored independent variable

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A multiple imputation method based on weighted quantile

Full text of "Nonparametric regression with nonparametrically generated covariates" See other formats The Annals of Statistics 2012, Vol. 40, No. 2, 1132-1170 DOI: 10.1214/12-AOS995 @ Institute of Mathematical Statistics, 2012 NONPARAMETRIC REGRESSION WITH NONPARAMETRICALLY GENERATED COVARIATES By Enno Mammen, Christoph Rothe and Melanie Schienle University of …

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Diagnostics for Confounding of Time-varying and Other

Mach Learn (2016) 102:323–348 DOI 10.1007/s10994-015-5527-7 Learning (predictive) risk scores in the presence of censoring due to interventions

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Overview of model validation for survival regression model

In the context of single failure time data, Qi and others found that using directly specified conditional MI methods for missing covariates gave estimates with large bias when the partially observed covariate was related to the censoring time.

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Missing covariates in competing risks analysis

AGeneralApproachforCureModels inSurvivalAnalysis Valentin Patilea for this task, a tool that provides a general ground for cure regression models. The idea is Recently, semiparametric models (like a single-index model as in Amico et al. 2017) or nonparametric models