Quantile regression under random censoring
By Bo E. Honoré, Shakeeb Khan, J. Powell. 2002
127 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/35bf7bffb5c167f7eb233aa5939cf32b2c621846
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Victor Chernozhukov
- Iv'an Fern'andez-Val
- Han Hong
- Shakeeb Khan
- Pedro H. C. Sant’Anna
- Alfred Galichon
- Elie Tamer
- Christian Hansen
In Management Science and Operations Research
- Victor Chernozhukov
- Iv'an Fern'andez-Val
- Elie Tamer
- Han Hong
- Pedro H. C. Sant’Anna
- Stephen Portnoy
- Shakeeb Khan
- Alfred Galichon
In Statistics and Probability
- Victor Chernozhukov
- Iv'an Fern'andez-Val
- Shakeeb Khan
- Lan Wang
- Han Hong
- Christian Hansen
- Alfred Galichon
- Pedro H. C. Sant’Anna
Citations in the corpus
- Subsampling Inference on Quantile Regression Processes (2005, methodology): “In addition, there are methods, developed in Buchinsky and Hahn (1998), Honoré, Khan and Powell (2002), Portnoy (2003) and Powell (1986), that account for censoring Subsampling inference on quantile regression processes 255 defined on an appropriately recentered empirical quantile regression…”
- Locally Weighted Censored Quantile Regression (2009, background): “Honoré, Khan, and Powell (2002) extended Powell’s approach to random censoring assuming that Ci is independent of both xi and Ti.”
- Three-Step Censored Quantile Regression and Extramarital Affairs (2002, background): “For example, in the famous Stanford survival dataset, we can compute all censoring points, because we know the transplant and the last follow-up dates for each i. In the extramarital affairs example, the censoring point is 0, Ci D 0. In this article we do not consider unobserved censoring points; Zh”
- Nonparametric Identification and Estimation of a Censored Location-Scale Regression Model (2005, background): “…important extension would be to allow for randomly censored datasets, as given by Buckley and James (1979), Koul, Suslara, and Van Ryzin (1981), Ying, Jung, and Wei (1995), and Honoré, Khan, and Powell (2002) for semiparametric models and by Van Keilegom and Akritas (1999) for nonparametric models.”
- QUANTILE AND PROBABILITY CURVES WITHOUT CROSSING (2007, background): “…known as 4See Koenker and Bassett (1978), Powell (1986), Chaudhuri (1991), Buchinsky and Hahn (1998), Yu and Jones (1998), Abadie et al. (2002), Honoré et al. (2002), and Chernozhukov and Hansen (2006), among others, for examples of exogenous, censored, endogenous, nonparametric, and other…”
- Nonparametric Tests for Treatment Effect Heterogeneity With Duration Outcomes (2016, background): “A particular case in which Assumption 2.2 is satisfied is when C is independent of (Y , X, T), as assumed by Bang and Tsiatis (2000), Anstrom and Tsiatis (2001), Honore, Khan, and Powell (2002), Lee and Lee (2005), Blundell and Powell (2007), among many others.”
- Partial rank estimation of duration models with general forms of censoring (2007, unknown): “PRE :0178 1⁄2 :0243; :0105 MRC (1987) :0140 1⁄2 :0370; :0105 MRE (1998) :0147 1⁄2 :0156; :0105 Honoré et al. (2002) :0134 1⁄2 :0162; :0111 Yang (1999) :0002 1⁄2 :0003; :0000 Ying et al.”
- Inference on endogenously censored regression models using conditional moment inequalities (2009, methodology): “Independence between ci and (xi, ǫi) was imposed in Ying, Jung, and Wei (1995), and Honoré, Khan, and Powell (2002) 8.”
- Survival Analysis With Quantile Regression Models (2008, background): “Honore, Khan, and Powell (2002) proposed parallel extension of Powell’s approach.”
- Censored Regression Quantiles (2003, background): “Some algorithmic progress and a number of applications have been given by Buchinsky and Hahn (1998), Fitzenberger (1997), Honoré, Khan, and Powell (2002), and Chernozhukovand Hong (2001), among others.”
- Inverse probability weighted estimation for general missing data problems (2004, unknown): “The linear regression model when ti yi has been studied by, among others, Buckley and James (1979), Koul, Susarla, and van Ryzin (1981) and, more recently, Honoré, Khan, and Powell (2002).”