癌症基因组研究信息披露的伦理探讨

癌症基因组计划是当前研究热点,存在诸多伦理、法律及社会问题,如何有效地保障基因组研究参与者的知情同意是值得关注的内容。信息披露(disclosure)作为知情同意的第一要素具备深厚的伦理基础,然而与传统医学研究相比,癌症基因组研究由于其目的与内容的特殊性,研究中信息披露的内容和标准尚存在诸多伦理问题,需要深入探讨。     

政府采购与经济增长的实证研究——基于ARMA最优模型

本文采用基于ARMA模型适用于小样本的最优预测的建模方法,来分析政府采购和经济增长之间的因果关系。研究结果表明政府采购和经济增长之间存在非对称、单向因果关系,即政府采购对经济增长的影响不显著,而经济增长对政府采购具有促进作用。因此,从政府采购影响路径的角度分析认为,在后金融危机时代应该采取一些可行的措施扭转政府采购对经济增长的不显著状况。     

Exploring Parameter Relations for Multi‐Stage Models in Stage‐Wise Constant and Time Dependent Hazard Rates

Single cohort stage‐frequency data are considered when assessing the stage reached by individuals through destructive sampling. For this type of data, when all hazard rates are assumed constant and equal, Laplace transform methods have been applied in the past to estimate the parameters in each stage‐duration distribution and the overall hazard rates. If hazard rates are not all equal, estimating stage‐duration parameters using Laplace transform methods becomes complex. In this paper, two new models are proposed to estimate stage‐dependent maturation parameters using Laplace transform methods where non‐trivial hazard rates apply. The first model encompasses hazard rates that are constant within each stage but vary between stages. The second model encompasses time‐dependent hazard rates within stages. Moreover, this paper introduces a method for estimating the hazard rate in each stage for the stage‐wise constant hazard rates model. This work presents methods that could be used in specific types of laboratory studies, but the main motivation is to explore the relationships between stage maturation parameters that, in future work, could be exploited in applying Bayesian approaches. The application of the methodology in each model is evaluated using simulated data in order to illustrate the structure of these models.     

On comparing,classifying and clustering several dependent regression models

Classifying several regression models fitted on a dataset is one of the most problems in data analysis. In other words, scientists are interested in comparing several regression models that can be used for a dataset. In this paper, an approach will be used to compare and classify several dependent regression models. Then the performance of the proposed method is investigated using simulation study and real example.     

Statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data

In this article, the statistical inference for the Gompertz distribution based on Type-II progressively hybrid censored data is discussed. The estimation of the parameters for Gompertz distribution is obtained using maximum likelihood method (MLE) and Bayesian method under three different loss functions. We also proved the existence and uniqueness of the MLE. The one-sample Bayesian prediction intervals are obtained. The work is done for different values of the parameters. We apply the Monto Carlo simulation to compare the proposed methods, also an example is discussed to construct the Prediction intervals.     

Inferences on regression coefficients in a regression model under heteroscedasticity and robustness with respect to departure from normality

In this paper we consider a simple linear regression model under heteroscedasticity and nonnormality. A statistical test for testing the regression coefficient is then derived by assuming normality for the random disturbances and by applying Welch's method. Some Monte Carlo studies are generated for assessing robustness of this test. By combining Tiku's robust procedure with the new test, a robust but more powerful test is developed.     

A process capability index with reliable confidence intervals

A well-know process capability index is slightly modified in this article to provide a new measure of process capability which takes account of the process location and variability, and for which point estimator and confidence intervals do exist that are insensitive to departures from the assumption of normal variability. Two examples of applications based on real data are presented.     

Smooth goodness of fit tests for the weibull distribution with singly censored data

The smooth goodness of fit tests are generalized to singly censored data and applied to the problem of testing Weibull (or extreme value) fit. Smooth tests, Pearson-type tests, and the spacings tests proposed by Mann, Schemer, and Fertig (1973) are compared on the basis of local asymptotic relative efficiency with respect to the asymptotic best test against generalized gamma alternatives, The smooth test of order one Is found to be most efficient for the generalized gamma alternatives.     

Kumulation von Mikrodaten – Konzeptionelle Grundlagen und ein Vorschlag zur Realisierung

Zusammenfassung: In dieser Studie wird ein Konzept zur Kumulation von laufenden Haushaltsbudgetbefragungen im Rahmen des Projektes Amtliche Statistik und sozioökonomische Fragestellungen entwickelt und zur Diskussion gestellt. Dafür werden die theoretischen Grundlagen und Bausteine gelegt und die zentrale Aufgabe einer strukturellen demographischen Gewichtung mit einem Hochrechnungs–/Kalibrierungsansatz auf informationstheoretischer Basis gelöst.Vor dem Hintergrund der Wirtschaftsrechnungen des Statistischen Bundesamtes (Lfd. Wirtschaftsrechnungen und EVS) wird darauf aufbauend ein konkretes Konzept für die Kumulation von jährlichen Haushaltsbudgetbefragungen vorgeschlagen. Damit kann das Ziel einer Kumulation von Querschnitten mit einer umfassenderen Kumulationsstichprobe für tief gegliederte Analysen erreicht werden. Folgen sollen die Simulationsrechnungen zur Evaluation des Konzepts.

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Summary: In this study a concept for cumulating periodic household surveys within the frame of the project Official Statistics and Socio–Economic Questions is developed and asks for discussion. We develop the theoretical background and solve the central task of a structural demographic weighting/calibration based on an information theoretical approach.Based on the household budget surveys of the Federal Statistical Office (Periodic Household Budget Surveys and Income and Consumption Sample (EVS)) a practical concept is proposed to cumulate yearly household surveys. This allows a cumulation of cross–sections by a comprehensive cumulated sample for deeply structured analyses. In a following study this concept shall be evaluated.

     

Optimal use of two auxiliary variables in double sampling

Double sampling scheme is used when cheap auxiliary variables may be measured to improve the estimation of a finite population parameter. Several estimators for population mean, ratio of means and variance are available, when two dependent samples are drawn. However, there are few proposals for the case of independent samples. In this paper both cases of dependent and independent samples are dealt with. A general approach for estimating a finite population parameter is given, showing that all the proposed estimators are particular cases of the same general class. The minimum variance bound for any estimator in this class is provided (at the first order of approximation). Furthermore, an optimal estimator which reaches this minimum is found.