In this paper, we introduce a generalized Liu estimator and jackknifed Liu estimator in a linear regression model with correlated or heteroscedastic errors. Therefore, we extend the Liu estimator. Under the mean squar...In this paper, we introduce a generalized Liu estimator and jackknifed Liu estimator in a linear regression model with correlated or heteroscedastic errors. Therefore, we extend the Liu estimator. Under the mean square error（MSE）, the jackknifed estimator is superior to the Liu estimator and the jackknifed ridge estimator. We also give a method to select the biasing parameter for d. Furthermore, a numerical example is given to illustvate these theoretical results.展开更多
The Cox proportional hazards model is the most used statistical model in the analysis of survival time data.Recently,a random weighting method was proposed to approximate the distribution of the maximum partial likeli...The Cox proportional hazards model is the most used statistical model in the analysis of survival time data.Recently,a random weighting method was proposed to approximate the distribution of the maximum partial likelihood estimate for the regression coefficient in the Cox model.This method was shown not as sensitive to heavy censoring as the bootstrap method in simulation studies but it may not be second-order accurate as was shown for the bootstrap approximation.In this paper,we propose an alternative random weighting method based on one-step linear jackknife pseudo values and prove the second accuracy of the proposed method.Monte Carlo simulations are also performed to evaluate the proposed method for fixed sample sizes.展开更多
This study aims to save cost of sampling for estimating the area under the amlodipine plasma concentration versus time curve in 24 hours(AUC0?24 h).Limited sampling strategy(LSS) models was developed and validated by ...This study aims to save cost of sampling for estimating the area under the amlodipine plasma concentration versus time curve in 24 hours(AUC0?24 h).Limited sampling strategy(LSS) models was developed and validated by mutilple regression model within 4 or fewer amlodipine concentration values.Absolute prediction error(APE),root of mean square error(RMSE) and visual predict check were used as criterion.The results of Jackknife validation showed that fifteen(9.4%) of the 160 LSS based on regression analysis were not within an APE of 15% by using one concentration-time point.156(97.5%),159(99.4%) and 160(100%) of the 160 LSS model were capable of predicting within an APE 15% by using 2,3,4 points,separately.Limited sampling strategies have been developed and validated for estimating AUC0?24 h of amlodipine.The present study indicated that the implemention of both 5 mg and 10 mg dosage could enable accurate predictions of AUC0?24 h by the same LSS model.This study shows that 12,4,24,2 h after administration are key sampling time points.The combination of(12,4),(12,4,24) or(12,4,24,2 h) might be chosen as sampling hours for predicting AUC0-24 h in practical application according to requirement.展开更多
基金Supported by the National Natural Science Foundation of China(11071022)Science and Technology Project of Hubei Provincial Department of Education(Q20122202)
文摘In this paper, we introduce a generalized Liu estimator and jackknifed Liu estimator in a linear regression model with correlated or heteroscedastic errors. Therefore, we extend the Liu estimator. Under the mean square error（MSE）, the jackknifed estimator is superior to the Liu estimator and the jackknifed ridge estimator. We also give a method to select the biasing parameter for d. Furthermore, a numerical example is given to illustvate these theoretical results.
基金supported by Natural Science and Engineering Research Council of Canada and National Natural Science Foundation of China(Grant No.10871188)
文摘The Cox proportional hazards model is the most used statistical model in the analysis of survival time data.Recently,a random weighting method was proposed to approximate the distribution of the maximum partial likelihood estimate for the regression coefficient in the Cox model.This method was shown not as sensitive to heavy censoring as the bootstrap method in simulation studies but it may not be second-order accurate as was shown for the bootstrap approximation.In this paper,we propose an alternative random weighting method based on one-step linear jackknife pseudo values and prove the second accuracy of the proposed method.Monte Carlo simulations are also performed to evaluate the proposed method for fixed sample sizes.
文摘This study aims to save cost of sampling for estimating the area under the amlodipine plasma concentration versus time curve in 24 hours(AUC0?24 h).Limited sampling strategy(LSS) models was developed and validated by mutilple regression model within 4 or fewer amlodipine concentration values.Absolute prediction error(APE),root of mean square error(RMSE) and visual predict check were used as criterion.The results of Jackknife validation showed that fifteen(9.4%) of the 160 LSS based on regression analysis were not within an APE of 15% by using one concentration-time point.156(97.5%),159(99.4%) and 160(100%) of the 160 LSS model were capable of predicting within an APE 15% by using 2,3,4 points,separately.Limited sampling strategies have been developed and validated for estimating AUC0?24 h of amlodipine.The present study indicated that the implemention of both 5 mg and 10 mg dosage could enable accurate predictions of AUC0?24 h by the same LSS model.This study shows that 12,4,24,2 h after administration are key sampling time points.The combination of(12,4),(12,4,24) or(12,4,24,2 h) might be chosen as sampling hours for predicting AUC0-24 h in practical application according to requirement.
