Discrete‐time survival trees

Tree‐based methods are frequently used in studies with censored survival time. Their structure and ease of interpretability make them useful to identify prognostic factors and to predict conditional survival probabilities given an individual's covariates. The existing methods are tailor‐made to deal with a survival time variable that is measured continuously. However, survival variables measured on a discrete scale are often encountered in practice. The authors propose a new tree construction method specifically adapted to such discrete‐time survival variables. The splitting procedure can be seen as an extension, to the case of right‐censored data, of the entropy criterion for a categorical outcome. The selection of the final tree is made through a pruning algorithm combined with a bootstrap correction. The authors also present a simple way of potentially improving the predictive performance of a single tree through bagging. A simulation study shows that single trees and bagged‐trees perform well compared to a parametric model. A real data example investigating the usefulness of personality dimensions in predicting early onset of cigarette smoking is presented. The Canadian Journal of Statistics 37: 17‐32; 2009 © 2009 Statistical Society of Canada     

Three enigmatic examples and inference from likelihood

Statistics has many inference procedures for examining a model with data to obtain information concerning the value of a parameter of interest. If these give different results for the same model and data, one can reasonably want a satisfactory explanation. Over the last eighty years, three very simple examples have appeared intermittently in the literature, often with contradictory or misleading results; these enigmatic examples come from Cox, Behrens, and Box & Cox. The procedures in some generality begin with an observed likelihood function, which is known to provide just first order accuracy unless there is additional information that calibrates the parameter. In particular, default Bayes analysis seeks such calibration in the form of a model‐based prior; such a prior with second order accuracy is examined for the Behrens problem, but none seems available for the Box and Cox problem. Alternatively, higher‐order likelihood theory obtains such information by examining likelihood at and near the data and achieves third order accuracy. We examine both Bayesian and frequentist procedures in the context of the three enigmatic examples; simulations support the indicated accuracies. The Canadian Journal of Statistics © 2009 Statistical Society of Canada     

试谈佛山孔庙学童开笔礼

佛山孔庙学童开笔礼,在继承学童入学拜孔子礼俗的基础上进行了地方化的改造,产生了良好的社会效应。佛山孔庙学童开笔礼作为一个新的文化品牌,获得了乡土知识与民间智慧的价值,不但可以弘扬儒家文化,还能使文化与经济发展产生互动。     

农林牧渔业人力资源现状与农学教育发展对策研究

近20年来,我国农林牧渔业从业人员的规模减少了22.2%,从业人员逐步呈现老龄化的趋势；从业人员的受教育程度有一定进步,但总体水平依然严重偏低；农业技术人员占第一产业从业人员的比例仅为0.1%。据预测,2020年第一产业从业人员总规模将下降为2.5亿人左右,大专及以上的比例由2010年的0.6%提高到2%,高中文化程度的比例由2010年的5.8%提高到12%。为达到上述目标,未来10年,农学本科专业的年平均招生人数应由目前的7.5万人上升为10万人；农学专科专业的年平均招生人数应由目前的7.6万人上升为23万人。因此课题组建议：加快农学高等教育规模发展,调整本专科招生比例；出台系列优惠政策,大力扶持农学高等教育发展；稳定中职招生规模,鼓励办学形式和教学模式的多样化发展；以多种形式、多种途径、多种机制积极发展农村职业技术培训；加大对高等学校和中职涉农专业毕业生的创业扶持,培养更多科技兴农的带头人。     

小学语文群文阅读教学策略浅析

群文阅读是对传统语文阅读教学方式的有效补充和重要创新,它在发展学生的高阶思维能力和阅读能力等方面有着重要作用,其最终目的是在学生学会阅读的基础上,落实学科核心素养。本文在对群文阅读进行理论分析的基础上,对小学语文教学中开展群文阅读的教学策略进行浅析。