An Algorithm for Unconstrained Quadratically Penalized Convex Optimization

Estimators are often defined as the solutions to data dependent optimization problems. A common form of objective function (function to be optimized) that arises in statistical estimation is the sum of a convex function V and a quadratic complexity penalty. A standard paradigm for creating kernel-based estimators leads to such an optimization problem. This article describes an optimization algorithm designed for unconstrained optimization problems in which the objective function is the sum of a non negative convex function and a known quadratic penalty. The algorithm is described and compared with BFGS on some penalized logistic regression and penalized L ^3/2 regression problems.     

An improved comorbidity summary score for measuring disease burden and predicting mortality with applications to two national cohorts

Abstract

Research involving administrative healthcare data to study patient outcomes requires the investigator to account for the patient’s disease burden in order to reduce the potential for biased results. Here we develop a comorbidity summary score based on variable importance measures derived from several statistical and machine learning methods and show it has superior predictive performance to the Elixhauser and Charlson indices when used to predict 1-year, 5-year, and 10-year mortality. We used two large Veterans Administration cohorts to develop and validate the summary score and compared predictive performance using the area under ROC curve (AUC) and the Brier score.     

A Multiple Imputation Approach to the Analysis of Current Status Data with the Additive Hazards Model

This article discusses regression analysis of current status data, which occur in many fields including cross-sectional studies, demographical investigations, and tumorigenicity experiments (Keiding, 1991 Keiding , N. ( 1991 ). Age-specific incidence and prevalence: a statistical perspective (with discussion) . J. Roy. Statist. Soc. Ser. A 154 : 371 – 412 .[Crossref] , [Google Scholar]; Sun 2006 Sun , J. ( 2006 ). The Statistical Analysis of Interval-Censored Failure Time Data . New York : Springer-Verlag . [Google Scholar]). For the problem, we focus on the situation where the survival time of interest can be described by the additive hazards model and a multiple imputation approach is presented for inference. A major advantage of the approach is its simplicity and it can be easily implemented by using the existing software packages for right-censored failure time data. Extensive simulation studies are conducted and indicate that the approach performs well for practical situations and is comparable to the existing methods. The methodology is applied to a set of current status data arising from a tumorigenicity experiment and the model checking is discussed.     

Assessing student learning in the context of evaluating a chance course

This paper describes the use of different assessment methods to evaluate Chance courses in the NSF-funded Chance project. Multiple methods were used to measure changes in students' attitudes and beliefs about statistics, reasoning about probability and statistics, and ability to critique a newspaper article that reports statistical results. Samples of assessment materials and scoring rubrics used in the evaluation are included.     

How Do Behavioral Assumptions Affect Structural Inference? Evidence From a Laboratory Experiment

We develop a model of labor force status (federal employment, nonfederal employment, unemployment, and out of the labor force) that depends on human capital variables, local labor market conditions, and personal characteristics. According to the estimated model for white non-Hispanic males and females a substantial difference exists between blacks and white non-Hispanics even after correction for the control variables. However, the control variables explain almost all of the difference between Hispanics and white non-Hispanics.     

The Increasingly Mixed Proportional Hazard Model: An Application to Socioeconomic Status,Health Shocks,and Mortality

We introduce a duration model that allows for unobserved cumulative individual-specific shocks, which are likely to be important in explaining variations in duration outcomes, such as length of life and time spent unemployed. The model is also a useful tool in situations where researchers observe a great deal of information about individuals when first interviewed in surveys but little thereafter. We call this model the “increasingly mixed proportional hazard” (IMPH) model. We compare and contrast this model with the mixed proportional hazard (MPH) model, which continues to be the workhorse of applied single-spell duration analysis in economics and the other social sciences. We apply the IMPH model to study the relationships among socioeconomic status, health shocks, and mortality, using 19 waves of data drawn from the German Socio-Economic Panel (SOEP). The IMPH model is found to fit the data statistically better than the MPH model, and unobserved health shocks and socioeconomic status are shown to play powerful roles in predicting longevity.     

高等农业职业教育《淡水养殖水化学》开展研究性学习的探索

国际 2 1世纪教育委员会的报告《教育———财富蕴藏其中》中提出面对未来社会的发展的 4种基本要求———学会认知、学会做事、学会共处、学会生存。这说明 ,在现代教育中 ,必须以学生发展为中心 ,开展研究性学习。我国实施的研究性学习就是改变我国传统的以教师为中心的教学模式 ,突出学生在学习中的主导地位。从贯彻素质教育的宗旨出发 ,在学科教学中渗透研究性学习 ,是培养学生综合能力的一种尝试和实践。     

浅析网络语言英语化的特点及发展趋势

随着因特网的迅速发展和英语全球化趋势的加快,网络中出现了大量的网络时尚英语,本文从网络语言中有大量英语缩略词、英译词等四个方面分析了网络语言英语化的特点,认为网络语言英语化将朝双语化、超口语化、虚拟化、弱语法化和重应用化方向发展。     

浅谈高校英语教师所应具备的素质

精读课是英语专业学生的一门主修课.精读教师的素质对教学质量以及大学生素质的培养起着关键性的作用.本文从精度课角度简单分析了高校英语教师应具备的素质--能力素质和思想道德素质.     

学习型组织综合评价方法的研究

将学习型组织系统划分为学习、组织、人员、知识和信息五个子系统,对五个子系统进行了系统的分析,在此基础上建立了学习型组织综合评价指标体系,采用层次分析法确定了各指标的权重,并运用模糊综合评价法建立了学习型组织的模糊评价模型。该模型为衡量一个组织向学习型组织转变的程度提供了理论依据。