语言哲学视阈下的隐喻研究

20世纪国外语言学界对隐喻研究的一个显著特点是从语义学向语言哲学的转向.在这一过程中,Black、Searle、White、Davison、Lakoff和Johnson等学者对隐喻的研究作出了各自的贡献,加深了人们对隐喻的认知机制及其认识论基础的理解.语言哲学的隐喻研究成果为语言研究提供了一个崭新的视角,隐喻研究也因此成为哲学研究的一个热点.     

Approximations to the distribution of weighted combination of independent probabilities

Two simple approximations are proposed for the distribution of the weighted combina-tion of n independent probabilities. The approximations are compared with other avail-able approximations. It is shown that one of the proposed approximations is better than the other approximations.     

约翰逊与美国的教育平等化改革

约翰逊总统60年代的社会改革是美国联邦教育政策形成的关键期,通过广泛的教育立法,对各级学校及贫困学生进行了大量的资助,美国联邦奠定了教育平等化的发展方向,促进了教育事业的发展及社会文明的整体提高。其以教育作为解决社会贫困及公平问题的重要手段,值得进行深刻的历史思考。     

A SELECTED BIBLIOGRAPHY ON THE ANALYSIS OF REPEATED MEASUREMENTS and RELATED AREAS

Different approaches to the analysis of repeated measurements are outlined. For each approach, a few key references are given as a possible basis for further reading. Related methodological areas are mentioned, again accompanied by key references in each case.     

Modeling fetal-growth biometry with Response Modeling Methodology (RMM) and comparison to current models

Monitoring fetal growth via ultrasound requires modeling fetal biometry in terms of gestation age. In this study, we compare Response Modeling Methodology (RMM) to current models, in three stages. First, RMM is used to approximate 47 empirical mean models that have appeared in the literature resulting in models with negligible loss in accuracy (unlike two other commonly applied models). Next, RMM models are fitted to sample averages of the Singaporean population and compared to a formerly published model. A similar simulation-based analysis is performed in the last stage for raw data of the British population. Altogether over 70 comparisons had been performed resulting in RMM consistently delivering better performing models.     

A trajectory analysis of body mass index for Finnish children

The aim of this study is to investigate the early development of body mass index (BMI), a standard tool for assessing the body shape and average level of adiposity for children and adults. The main aim of the study is to identify the primary trajectories of BMI development and to investigate the changes of certain growth characteristics over time. Based on our longitudinal data of 4223 Finnish children, we took anthropometric measurements from birth up to 15 years of age for birth years 1974, 1981, 1991 and 1995, but only up to 11 years of age for the birth year 2001. As a statistical method, we utilized trajectory analysis with the methods of nonparametric regression. We identified four main trajectories of BMI growth. Two of these trajectories do not seem to follow the normal growth pattern. The highest growth track appears to yield to a track that may yield to overweight and the low birth BMI track shows that the girls’ track differs that of boys on the same track, and on the normal tracks. The so-called adiposity rebound time decreased over time and started earlier for those on the overweight track. According to our study, this kind of acceleration of growth might be more of a general phenomenon that also relates to the other phases of BMI development. The major change seems to occur especially for those children on high growth tracks.     

An application of multinomial logistic regression to estimating performance of a multiple-screening test with incomplete verification

Summary.  The paper describes a method of estimating the performance of a multiple-screening test where those who test negatively do not have their true disease status determined. The methodology is motivated by a data set on 49927 subjects who were given K =6 binary tests for bowel cancer. A complicating factor is that individuals may have polyps in the bowel, a condition that the screening test is not designed to detect but which may be worth diagnosing. The methodology is based on a multinomial logit model for Pr( S | R ₆), the probability distribution of patient status S (healthy, polyps or diseased) conditional on the results R ₆ from six binary tests. An advantage of the methodology described is that the modelling is data driven. In particular, we require no assumptions about correlation within subjects, the relative sensitivity of the K tests or the conditional independence of the tests. The model leads to simple estimates of the trade-off between different errors as the number of tests is varied, presented graphically by using receiver operating characteristic curves. Finally, the model allows us to estimate better protocols for assigning subjects to the disease group, as well as the gains in accuracy from these protocols.     

Robust estimation in growth curve models

The growth curve model introduced by potthoff and Roy 1964 is a general statistical model which includes as special cases regression models and both univariate and multivariate analysis of variance models. The methods currently available for estimating the parameters of this model assume an underlying multivariate normal distribution of errors. In this paper, we discuss tw robst estimators of the growth curve loction and scatter parameters based upon M-estimation techniques and the work done by maronna 1976. The asymptotic distribution of these robust estimators are discussed and a numerical example given.     

Functional linear discriminant analysis for irregularly sampled curves

We introduce a technique for extending the classical method of linear discriminant analysis (LDA) to data sets where the predictor variables are curves or functions. This procedure, which we call functional linear discriminant analysis ( FLDA ), is particularly useful when only fragments of the curves are observed. All the techniques associated with LDA can be extended for use with FLDA. In particular FLDA can be used to produce classifications on new (test) curves, give an estimate of the discriminant function between classes and provide a one- or two-dimensional pictorial representation of a set of curves. We also extend this procedure to provide generalizations of quadratic and regularized discriminant analysis.     

A resampling‐based test for two crossing survival curves

The area between two survival curves is an intuitive test statistic for the classical two‐sample testing problem. We propose a bootstrap version of it for assessing the overall homogeneity of these curves. Our approach allows ties in the data as well as independent right censoring, which may differ between the groups. The asymptotic distribution of the test statistic as well as of its bootstrap counterpart are derived under the null hypothesis, and their consistency is proven for general alternatives. We demonstrate the finite sample superiority of the proposed test over some existing methods in a simulation study and illustrate its application by a real‐data example.