This study has found that there is a potential role for ProGRP and NSE in both therapy monitoring and predicting survival in SCLC patients.

In this thesis, we are interested in empirical likelihood (EL) methods for twosample problems, with focus on the difference of the two population means. A weighted empirical likelihood method (WEL) for two-sample problems is developed . We also consider a scenario where sample data on auxiliary variables are fully observed for both samples but values of the response variable are subject to missingness. We develop an adjusted empirical likelihood method for inference of the difference of the two population means for this scenario where missing values are handled by a regression imputation method. Bootstrap calibration for WEL is also developed. Simulation studies are conducted to evaluate the performance of naive EL, WEL and WEL with bootstrap calibration (BWEL) with comparison to the usual two-sample t-test in terms of power of the tests and coverage accuracies. Simulation for the adjusted EL for the linear regression model with missing data is also conducted.iii

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Background: This study aims to investigate the association between handgrip strength (HGS) and cardiometabolic disorders (CMD), including hypertension, diabetes, and dyslipidemia, in a prospective study. Methods: The association between HGS and CMD was examined using the data from 5,271 Chinese adult participants ≥45 years old enrolled in the CHARLS (Chinese Health and Retirement Prospective Cohort Study) during 2011-2015. Relative HGS, calculated as maximal absolute HGS from both hands divided by body mass index, was used in the primary analysis and divided into three groups according to the tertiles (T1, T2, and T3). Results: The participants with higher relative HGS had a lower risk of hypertension, diabetes, and dyslipidemia than those with lower HGS, although did not reach statistical significance for diabetes and hypertension in males. Participants with higher HGS had significantly lower risk of hypertension [T3 vs. T1: OR = 0.69, 95% CI = 0.51-0.91, P = 0.010] and dyslipidemia (OR = 0.65, 95% CI = 0.51-0.83, P < 0.001) in males. For females, participants with higher HGS had significantly lower risks of dyslipidemia (OR = 0.67, 95% CI = 0.54-0.83, P < 0.001). Conclusion: A consistent association was observed between higher relative HGS and lower risk of CMD. Further research is required to evaluate whether relative HGS can be a convincing predictor for the occurrence of CMD and as a target for intervention in the high-risk population.

In survival analysis, covariate measurement error has been studied extensively for the Cox model. In this article, we propose a corrected profile likelihood approach, and show that many existing methods can be unified by our approach. Furthermore, we extend our discussion to general measurement error and Berkson models, as opposed to the classical additive error model that has been widely used in the literature. We investigate the impact of model misspecification of the measurement error process and uncover interesting findings. Empirical studies are carried out to illustrate the usage of the proposed methods and to assess their performance. The Canadian Journal of Statistics 43: 454–480; 2015 © 2015 Statistical Society of Canada