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This kind of result usually is called a Bahadur representation. For the case where [F. Correspondingly, for the case that [F.


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These sharp results involve considerable effort. In this article we give a general result Theorem 1 stating that under regularity conditions on F must be smooth and strictly increasing but does not have to be a distribution function , if 1. From a statistical applications standpoint this is all that is needed, because it is enough to infer a weak convergence result for the quantile process.

The idea in the proof of Theorem 1 is based on a lemma of Vervaat and seems to be known see, Shorack and Wellner , pp. Censored quantile regression with high-dimensional features. Discussion and future directions. Conflict of interest. Quantile regression for survival data in modern cancer research: expanding statistical tools for precision medicine Hyokyoung G Hong.

Oxford Academic. Google Scholar. David C Christiani. Yi Li. Correspondence: Yi Li, yili umich. Cite Citation. Permissions Icon Permissions. Abstract Quantile regression links the whole distribution of an outcome to the covariates of interest and has become an important alternative to commonly used regression models. We begin by introducing the concept of quantiles, followed by censored quantile regression. When the quantile is defined based on the distribution of T alone, without considering covariates, X , it is called the marginal quantile or unconditional quantile.

A quantile regression describes how the covariate or covariate vector of interest impacts the conditional quantiles of the outcome. Figure 1. Open in new tab Download slide. Figure 2.

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Figure 3. Selected CpG sites related to the 0. Precision medicine screening using whole-genome sequencing and advanced imaging to identify disease risk in adults. Search ADS. Delivery of cascade screening for hereditary conditions: A scoping review of the literature. Integration of genomics, high throughput drug screening, and personalized xenograft models as a novel precision medicine paradigm for high risk pediatric cancer. Breast cancer risk factors, survival and recurrence, and tumor molecular subtype: analysis of women from an indigenous Asian population.

A comparison between accelerated failure-time and Cox proportional hazard models in analyzing the survival of gastric cancer patients. Dose-escalated irradiation and overall survival in men with nonmetastatic prostate cancer. Role of Epigenetics in Cancer Initiation and Progression. Advances in Experimental Medicine and Biology , vol Springer, New York, NY, Crosstalk between epigenetics and metabolism- Yin and Yang of histone demethylases and methyltransferases in cancer. DNA methylation biomarkers in lung cancer diagnosis: closer to practical use? Aberrant DNA methylation in non-small cell lung cancer-associated fibroblasts.

12. Testing Goodness of Fit (cont.)

Obesity, metabolic factors and risk of different histological types of lung cancer: A Mendelian randomization study. The heterogeneity in risk factors of lung cancer and the difference of histologic distribution between genders in Taiwan. Application of censored quantile regression to determine overall survival related factors in breast cancer. Robust identification of gene-environment interactions for prognosis using a quantile partial correlation approach. Prediction of functional status for the elderly based on a new ordinal regression model.

Thinking beyond the mean: a practical guide for using quantile regression methods for health services research. Feature selection of ultrahigh-dimensional covariates with survival outcomes: a selective review. Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data. A CpG-methylation-based assay to predict survival in clear cell renal cell carcinoma.

Semiparametric analysis of interval-censored survival data with median regression model. Springer, Cham, For commercial re-use, please contact journals. Issue Section:. Download all figures.

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