scholarly journals Corrected-loss estimation for quantile regression with covariate measurement errors

Biometrika ◽  
2012 ◽  
Vol 99 (2) ◽  
pp. 405-421 ◽  
Author(s):  
H. J. Wang ◽  
L. A. Stefanski ◽  
Z. Zhu
2024 ◽  
Author(s):  
Mengli Zhang ◽  
Lan Xue ◽  
Carmen D. Tekwe ◽  
Yang Bai ◽  
Annie Qu

Author(s):  
Lara Gerdessen ◽  
Patrick Meybohm ◽  
Suma Choorapoikayil ◽  
Eva Herrmann ◽  
Isabel Taeuber ◽  
...  

Abstract Estimating intraoperative blood loss is one of the daily challenges for clinicians. Despite the knowledge of the inaccuracy of visual estimation by anaesthetists and surgeons, this is still the mainstay to estimate surgical blood loss. This review aims at highlighting the strengths and weaknesses of currently used measurement methods. A systematic review of studies on estimation of blood loss was carried out. Studies were included investigating the accuracy of techniques for quantifying blood loss in vivo and in vitro. We excluded nonhuman trials and studies using only monitoring parameters to estimate blood loss. A meta-analysis was performed to evaluate systematic measurement errors of the different methods. Only studies that were compared with a validated reference e.g. Haemoglobin extraction assay were included. 90 studies met the inclusion criteria for systematic review and were analyzed. Six studies were included in the meta-analysis, as only these were conducted with a validated reference. The mixed effect meta-analysis showed the highest correlation to the reference for colorimetric methods (0.93 95% CI 0.91–0.96), followed by gravimetric (0.77 95% CI 0.61–0.93) and finally visual methods (0.61 95% CI 0.40–0.82). The bias for estimated blood loss (ml) was lowest for colorimetric methods (57.59 95% CI 23.88–91.3) compared to the reference, followed by gravimetric (326.36 95% CI 201.65–450.86) and visual methods (456.51 95% CI 395.19–517.83). Of the many studies included, only a few were compared with a validated reference. The majority of the studies chose known imprecise procedures as the method of comparison. Colorimetric methods offer the highest degree of accuracy in blood loss estimation. Systems that use colorimetric techniques have a significant advantage in the real-time assessment of blood loss.


2020 ◽  
pp. 096228022094153
Author(s):  
Yongxin Bai ◽  
Maozai Tian ◽  
Man-Lai Tang ◽  
Wing-Yan Lee

In this paper, we consider variable selection for ultra-high dimensional quantile regression model with missing data and measurement errors in covariates. Specifically, we correct the bias in the loss function caused by measurement error by applying the orthogonal quantile regression approach and remove the bias caused by missing data using the inverse probability weighting. A nonconvex Atan penalized estimation method is proposed for simultaneous variable selection and estimation. With the proper choice of the regularization parameter and under some relaxed conditions, we show that the proposed estimate enjoys the oracle properties. The choice of smoothing parameters is also discussed. The performance of the proposed variable selection procedure is assessed by Monte Carlo simulation studies. We further demonstrate the proposed procedure with a breast cancer data set.


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