德国“双元制”模式对我国职业教育发展的启示与思考

德国的职业教育为德国经济的发展提供了极为重要的智力支持，被誉为经济发展的“秘密武器”。双元制模式是德国职业教育成功的实践模式，对我国职业教育的发展有着非常重要的启示和借鉴作用。从发达国家中汲取有利于发展我国职业教育的经验，使职业教育由弱势走向强盛，由传统教育体系的附属走向终身教育体系的主体，意义重大而深远。     

A critical evaluation of competing representations of the relationship between formal and informal work

Analysing the extensive literature on informal work reveals multiple, often contradictory, views regarding its relationship with formal work. The aim of this paper is to evaluate critically these competing claims. Evaluating in turn the predominant views of informal work as a residue, by-product, complement and/or alternative to formal work, reveals that universal generalizations are not possible and that all of these articulations only apply in specific contexts. However, rather than simply conclude that these contrasting readings of the relationship between informal and formal work are therefore context-bound generalizations, two features common to all these perspectives are identified that necessitate a more fundamental rethinking of the relationship between formal and informal work. These relate to the way in which all firstly, simplistically attribute one form of work with positive features (e.g. modernization, virtue and progress) and the other with negative attributes (e.g. tradition, backwardness, exploitation) and, secondly, delineate formal and informal work as discrete and separate entities. The paper concludes by setting out a research agenda to not only highlight the political values underpinning each of these representations but also achieve a fuller and finer-grained understanding of the relations between informal and formal work.     

基于Logistic回归分析的土地利用变化空间统计与模拟

运用二元Logistic回归分析的方法,对研究区域土地利用/覆盖变化有重要贡献的10种驱动因子进行空间统计分析,并用ROC方法对所有回归模型的拟合优度进行了检验,运用GIS软件绘制研究区土地利用格局空间分布的经验统计概率图。ROC检验结果显示:各种土地类型的拟合度分别为耕地0.761,林地0.844,草地0.673,水域0.859,建设用地0.937,拟合度均大于0.5,拟合度较好;研究结果揭示了距县城中心的距离(X2)、高程(X6)、坡度(X7)、坡向(X8)、人口密度(X9)因素对研究区土地利用格局形成与演变有重要决定作用,为进一步研究黄土高原地区未来的土地利用动态变化情景奠定了基础,同时也为该地区的土地利用管理提供了科学依据。     

Curtailed two-stage designs with two dependent binary endpoints

When phase I clinical trials were found to be unable to precisely estimate the frequency of toxicity, Brayan and Day proposed incorporating toxicity considerations into two-stage designs in phase II clinical trials. Conaway and Petroni further pointed out that it is important to evaluate the clinical activity and safety simultaneously in studying cancer treatments with more toxic chemotherapies in a phase II clinical trial. Therefore, they developed multi-stage designs with two dependent binary endpoints. However, the usual sample sizes in phase II trials make these designs difficult to control the type I error rate at a desired level over the entire null region and still have sufficient power against reasonable alternatives. Therefore, the curtailed sampling procedure summarized by Phatak and Bhatt will be applied to the two-stage designs with two dependent binary endpoints in this paper to reduce sample sizes and speed up the development process for drugs.     

Impact of safety monitoring on error probabilities of binary efficacy outcome analyses in large phase III group sequential trials

In phase III clinical trials, some adverse events may not be rare or unexpected and can be considered as a primary measure for safety, particularly in trials of life-threatening conditions, such as stroke or traumatic brain injury. In some clinical areas, efficacy endpoints may be highly correlated with safety endpoints, yet the interim efficacy analyses under group sequential designs usually do not consider safety measures formally in the analyses. Furthermore, safety is often statistically monitored more frequently than efficacy measures. Because early termination of a trial in this situation can be triggered by either efficacy or safety, the impact of safety monitoring on the error probabilities of efficacy analyses may be nontrivial if the original design does not take the multiplicity effect into account. We estimate the actual error probabilities for a bivariate binary efficacy-safety response in large confirmatory group sequential trials. The estimated probabilities are verified by Monte Carlo simulation. Our findings suggest that type I error for efficacy analyses decreases as efficacy-safety correlation or between-group difference in the safety event rate increases. In addition, although power for efficacy is robust to misspecification of the efficacy-safety correlation, it decreases dramatically as between-group difference in the safety event rate increases.     

Average kappa coefficient: a new measure to assess a binary test considering the losses associated with an erroneous classification

The weighted kappa coefficient of a binary diagnostic test (BDT) is a measure of performance of a BDT, and is a function of the sensitivity and the specificity of the diagnostic test, of the disease prevalence and the weighting index. Weighting index represents the relative loss between the false positives and the false negatives. In this study, we propose a new measure of performance of a BDT: the average kappa coefficient. This parameter is the average function of the weighted kappa coefficients and does not depend on the weighting index. We have studied three asymptotic confidence intervals (CIs) for the average kappa coefficient, Wald, logit and bias-corrected bootstrap, and we carried out some simulation experiments to study the asymptotic coverage of each of the three CIs. We have written a program in R, called ‘akcbdt’, to estimate the average kappa coefficient of a BDT. This program is available as supplementary material. The results were applied to two examples.     

GEEs for repeated categorical responses based on generalized residuals

Clustered or correlated samples of categorical response data arise frequently in many fields of application. The method of generalized estimating equations (GEEs) introduced in Liang and Zeger [Longitudinal data analysis using generalized linear models, Biometrika 73 (1986), pp. 13–22] is often used to analyse this type of data. GEEs give consistent estimates of the regression parameters and their variance based upon the Pearson residuals. Park et al. [Alternative GEE estimation procedures for discrete longitudinal data, Comput. Stat. Data Anal. 28 (1998), pp. 243–256] considered a modification of the GEE approach using the Anscombe residual and the deviance residual. In this work, we propose to extend this idea to a family of generalized residuals. A wide simulation study is conducted for binary and Poisson correlated outcomes and also two numerical illustrations are presented.     

A finite sample comparison of nonparametric estimates of the effective dose in quantal bioassay

To estimate the effective dose level ED_α in the common binary response model, several parametric and nonparametric estimators have been proposed in the literature. In the present article, we focus on nonparametric methods and present a detailed numerical comparison of four different approaches to estimate the ED_α nonparametrically. The methods are briefly reviewed and their finite sample properties are studied by means of a detailed simulation study. Moreover, a data example is presented to illustrate the different concepts.     

Trends in smoking cessation: a Markov model approach

Intervention trials such as studies on smoking cessation may observe multiple, discrete outcomes over time. When the outcome is binary, participant observations may alternate between two states over the course of the study. The generalized estimating equation (GEE) approach is commonly used to analyze binary, longitudinal data in the context of independent variables. However, the sequence of observations may be assumed to follow a Markov chain with stationary transition probabilities when observations are made at fixed time points. Participants favoring the transition to one particular state over the other would be evidence of a trend in the observations. Using a log-transformed trend parameter, the determinants of a trend in a binary, longitudinal study may be evaluated by maximizing the likelihood function. A new methodology is presented here to test for the presence and determinants of a trend in binary, longitudinal observations. Empirical studies are evaluated and comparisons are made with the GEE approach. Practical application of the proposed method is made to the data available from an intervention study on smoking cessation.     

Measuring resetting of brain dynamics at epileptic seizures: application of global optimization and spatial synchronization techniques

Epileptic seizures are manifestations of intermittent spatiotemporal transitions of the human brain from chaos to order. Measures of chaos, namely maximum Lyapunov exponents (STL _max ), from dynamical analysis of the electroencephalograms (EEGs) at critical sites of the epileptic brain, progressively converge (diverge) before (after) epileptic seizures, a phenomenon that has been called dynamical synchronization (desynchronization). This dynamical synchronization/desynchronization has already constituted the basis for the design and development of systems for long-term (tens of minutes), on-line, prospective prediction of epileptic seizures. Also, the criterion for the changes in the time constants of the observed synchronization/desynchronization at seizure points has been used to show resetting of the epileptic brain in patients with temporal lobe epilepsy (TLE), a phenomenon that implicates a possible homeostatic role for the seizures themselves to restore normal brain activity. In this paper, we introduce a new criterion to measure this resetting that utilizes changes in the level of observed synchronization/desynchronization. We compare this criterion’s sensitivity of resetting with the old one based on the time constants of the observed synchronization/desynchronization. Next, we test the robustness of the resetting phenomena in terms of the utilized measures of EEG dynamics by a comparative study involving STL _max , a measure of phase (φ _max ) and a measure of energy (E) using both criteria (i.e. the level and time constants of the observed synchronization/desynchronization). The measures are estimated from intracranial electroencephalographic (iEEG) recordings with subdural and depth electrodes from two patients with focal temporal lobe epilepsy and a total of 43 seizures. Techniques from optimization theory, in particular quadratic bivalent programming, are applied to optimize the performance of the three measures in detecting preictal entrainment. It is shown that using either of the two resetting criteria, and for all three dynamical measures, dynamical resetting at seizures occurs with a significantly higher probability (α=0.05) than resetting at randomly selected non-seizure points in days of EEG recordings per patient. It is also shown that dynamical resetting at seizures using time constants of STL _max synchronization/desynchronization occurs with a higher probability than using the other synchronization measures, whereas dynamical resetting at seizures using the level of synchronization/desynchronization criterion is detected with similar probability using any of the three measures of synchronization. These findings show the robustness of seizure resetting with respect to measures of EEG dynamics and criteria of resetting utilized, and the critical role it might play in further elucidation of ictogenesis, as well as in the development of novel treatments for epilepsy.