Survival Analysis With Quantile Regression Models

By Limin Peng, Yijian Huang. 2008

347 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/fd55a81dd800ed6a7694b2e2fa235f284de552c7

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In Statistics and Probability

Citations in the corpus

Locally Weighted Censored Quantile Regression (2009, result): “Recently, Peng and Huang (2008) proposed a martingale-based estimating procedure that showed similar performance to Portnoy’s estimator.”
Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data (2013, methodology): “As a powerful alternative to the classical Cox model, quantile regression has recently emerged as a useful tool for analyzing censored data, see Ying, Jung and Wei (1995), McKeague, Subramanian and Sun (2001), Portnoy (2003), Peng and Huang (2008), Wang and Wang (2009), among others.”
Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood (2016, methodology): “…D x>ˇ. /: (3.2) Various estimation methods have been developed for censored quantile regression, including Portnoy (2003), Ying et al. (1995), Peng & Huang (2008) and Wang & Wang (2009) for random censoring, Lin et al. (2012) for double censoring and Powell (1986) and Tang et al. (2012) for fixed…”
Optimal Bandwidth Selection for Nonparametric Conditional Distribution and Quantile Functions (2013, background): “…Bassett (1978) appeared, quantile regression has exploded in popularity and a range of innovative approaches toward the estimation of conditional quantiles has been proposed including Yu and Jones (1998), Koenker and Xiao (2004), Li, Liu, and Zhu (2007), and Peng and Huang (2008) to name but a few.”
Handbook of survival analysis (2014, methodology): “Peng and Huang (2008) established the uniform consistency and weak convergence of β̂PH(·).”
Quantile Correlations and Quantile Autoregressive Modeling (2012, neutral): “…data structures can be found in the literature , for example, Machado and Silva (2005) for count data, Mu and He (2007) for power transformed data, Peng and Huang (2008) and Wang and Wang (2009) for survival analysis, He and Liang (2000) and Wei and Carroll (2009) for regression with measurement…”
A quantile regression estimator for censored data (2013, methodology): “…simulation study, we compare the estimator of Ying et al. (YJW), the proposed estimator (CQR), the locally weighted censored quantile regression estimator (Lcrq) in Wang and Wang [22], the estimator in Portnoy [17], abbreviated as Port, and the estimator by Peng and Huang [16], abbreviated as PH.”
Censored Quantile Regression Redux (2008, methodology): “Recently, Portnoy (2003) and Peng and Huang (2008) have introduced new approaches to quantile regression for randomly censored observations.”
Estimation of Censored Quantile Regression for Panel Data With Fixed Effects (2013, background): “…1997; Buchinsky and Hahn 1998; Bilias, Chen, and Ying 2000; Khan and Powell 2001; Chernozhukov and Hong 2002; Honoré, Khan, and Powell 2002; Portnoy 2003; Peng and Huang 2008; Lin, He, and Portnoy 2012; Tang et al. 2012), the literature on censored QR for panel data is still very limited.”