《中华苏维埃共和国宪法》的再探讨

长期以来 ,史学界忽视了中华苏维埃共和国成立时 ,制定的《中华苏维埃共和国宪法》 ,极个别学者虽然引起了注意 ,但错误地把它混同于当时制定的《中华苏维埃共和国宪法草案》 ,我们认为《中华苏维埃共和国宪法》的存在是不容置疑的 ,1 931年 2月前 ,由中共中央和共产国际远东局共同起草 ,由于苏维埃政权当时还局限于中国的局部地区 ,故未提交“一苏大”讨论     

社会民主主义复兴的两种模式比较

20世纪90年代在社会民主主义复兴的过程中,英国和法国由于竞选方式、政策策略等一系列方面存在显著差别,被认为是社会民主主义复兴的两种典型模式,对英国道路与法国道路的相同之处和不同之处进行比较,说明二者存在共同性和差异性的原因。     

无理数e在电路基本理论中出现的物理意义

对无理数e在电路分析中出现的几个典型例子作了分析讨论，明确指出：由1／e决定的特征常数可以在时间分布上和空间分布上，把一个按指数规律非均匀变化的问题，用一个等效的均匀变化的问题来表示；可以反映初始变化率与最终稳定值之间的联系；可以更深刻地反映某些物理过程的本质特征。     

Still-births among the offspring of male radiation workers at the Sellafield nuclear reprocessing plant: detailed results and statistical aspects

Summary. This study investigates whether there was evidence of increasing risk of still-birth with increasing paternal exposure to ionizing radiation received during employment at the Sellafield nuclear installation before the child was conceived. A significant positive association is found between the total paternal preconceptional exposure to external ionizing radiation and the risk of still-birth (after adjustment for year of birth, social class, birth order and paternal age, odds ratio at 100 mSv 1.24 (95% confidence interval 1.04–1.45)). A summary of the principal scientific findings of this study has been published in the Lancet . This paper describes in detail the statistical methods that were used in the investigation and presents the results in full.     

Book Reviews

Books reviewed:
M Hollander and D Wolfe, Nonparametric Statistical Methods
T Leonard and J.S.J Hsu, Bayesian Methods     

测定小惯性热电偶时间常数新法

研究了用电加热法解决用于动态气流温度测量的小惯性热电偶时间常数的实验测定问题。提出采取在稳定气流场中用电加热热电偶然后迅速切断电源的方法 ,获取较为理想的负温度阶跃 ,进而由热电偶的阶跃响应曲线求得时间常数。设计了相应的设备 ,并进行了实验测定 ,获得了较好的结果。     

Modelling daily multivariate pollutant data at multiple sites

Summary. This paper considers the spatiotemporal modelling of four pollutants measured daily at eight monitoring sites in London over a 4-year period. Such multiple-pollutant data sets measured over time at multiple sites within a region of interest are typical. Here, the modelling was carried out to provide the exposure for a study investigating the health effects of air pollution. Alternative objectives include the design problem of the positioning of a new monitoring site, or for regulatory purposes to determine whether environmental standards are being met. In general, analyses are hampered by missing data due, for example, to a particular pollutant not being measured at a site, a monitor being inactive by design (e.g. a 6-day monitoring schedule) or because of an unreliable or faulty monitor. Data of this type are modelled here within a dynamic linear modelling framework, in which the dependences across time, space and pollutants are exploited. Throughout the approach is Bayesian, with implementation via Markov chain Monte Carlo sampling.     

论创造性思维的时效性

创造性思维的时效是指创造性思维在一定的时间内所取得的思维成果。在追求创造性思维科学性的同时 ,力求其高效率是创造性思维的目的。我们要运用先进的思维工具 ,采用科学的思维方法 ,尽量减少创造性思维中的挫折和曲折 ,力戒不必要思维时间的浪费 ,以提高创造性思维的效率     

Simple detection of outlying short time series

Sets of relatively short time series arise in many situations. One aspect of their analysis may be the detection of outlying series. We examine the performance of standard normal outlier tests applied to the means, or to simple functions of the means, of AR(1) series, not necessarily of equal lengths. Although unequal lengths of series implies that the means have unequal variances, that are only known approximately, it is shown that nominal significance levels hold good under most circumstances. Thus a standard outlier test can usefully be applied, avoiding the complication of estimating the time series' parameters. The test's power is affected by unequal lengths, being higher when the slippage occurs in one of the longer series     

Type I error rates from likelihood‐based repeated measures analyses of incomplete longitudinal data

The last observation carried forward (LOCF) approach is commonly utilized to handle missing values in the primary analysis of clinical trials. However, recent evidence suggests that likelihood‐based analyses developed under the missing at random (MAR) framework are sensible alternatives. The objective of this study was to assess the Type I error rates from a likelihood‐based MAR approach – mixed‐model repeated measures (MMRM) – compared with LOCF when estimating treatment contrasts for mean change from baseline to endpoint (Δ). Data emulating neuropsychiatric clinical trials were simulated in a 4 × 4 factorial arrangement of scenarios, using four patterns of mean changes over time and four strategies for deleting data to generate subject dropout via an MAR mechanism. In data with no dropout, estimates of Δ and SE_Δ from MMRM and LOCF were identical. In data with dropout, the Type I error rates (averaged across all scenarios) for MMRM and LOCF were 5.49% and 16.76%, respectively. In 11 of the 16 scenarios, the Type I error rate from MMRM was at least 1.00% closer to the expected rate of 5.00% than the corresponding rate from LOCF. In no scenario did LOCF yield a Type I error rate that was at least 1.00% closer to the expected rate than the corresponding rate from MMRM. The average estimate of SE_Δ from MMRM was greater in data with dropout than in complete data, whereas the average estimate of SE_Δ from LOCF was smaller in data with dropout than in complete data, suggesting that standard errors from MMRM better reflected the uncertainty in the data. The results from this investigation support those from previous studies, which found that MMRM provided reasonable control of Type I error even in the presence of MNAR missingness. No universally best approach to analysis of longitudinal data exists. However, likelihood‐based MAR approaches have been shown to perform well in a variety of situations and are a sensible alternative to the LOCF approach. MNAR methods can be used within a sensitivity analysis framework to test the potential presence and impact of MNAR data, thereby assessing robustness of results from an MAR method. Copyright © 2004 John Wiley & Sons, Ltd.