儒家真精神——“时中”

儒家时中是中和世界观和中庸方法论的统一 ,时中的内涵实质在依时而中、与时俱进 ,儒家的时中观包涵着深刻的唯物辩证思想 ,包含着强烈的适应进取精神 ,蕴涵着鲜明的知识理性内容。时中是儒家的真精神 ,是中华民族的真精神 ,是今天实现中华民族伟大复兴的真精神。     

客体特征统计属性表征机制的特异性

通过两个实验就视觉系统能否像计算平均数那样高效地计算其他统计量的问题进行了探讨。实验—保持—组圆的平均大小不变而改变众数,考察平均数估计是否受众数变化的影响;实验二采用与实验一相同的刺激,直接考察被试估计众数的绩效。结果发现：（1）对平均数的估计不受总体众数变化的影响;（2）对众数的估计往往不如对平均数的估计准确,估计值受平均数变化的影响;（3）在估计众数的任务中,被试成绩受总体极大值的影响。上述结果表明,视觉系统不存在针对众数的自动化加工机制。根据本实验的结果可以进一步推测,视觉系统并非对所有统计量都可做高效加工,而可能存在针对平均数的特异加工机制。     

Analysis of unreplicated three-way classifications,with applications to rater bias and trait independence

The seven analysis-of-variance mean squares for an unreplicated three-way classification may be written as linear combinations of a mean variance and three mean covariances. Formulas are presented for computing the mean variances and mean covariances from linear combinations of mean squares. The relevance of these formulas for assessing rater biases and trait independence is discussed, a numerical example is provided, and proposed extensions are briefly noted.The research reported herein was performed pursuant to a contract with the United States Office of Education, Department of Health, Education, and Welfare. The assistance of Sister M. Jacinta Mann, S. C., at one stage of this investigation is gratefully acknowledged.     

Analyzing coefficients of psychophysical power functions

Somemathematical properties of coefficients of power functions were analyzed. The size of correlations between intercepts (the logarithm of the coefficient) andexponent.s depends on the choice of unit of measurement of the physical stimuli. When the mean of logarithms of a set of responses is uncorrelated with the exponent, the absolute size of the correlation between the intercept and the exponent increases as the geometricmean of the stimulus measures deviatesfrom one. When the geometric mean is less than one, the correlation is positive, and when it is greater than one, the correlation is negative. Similar trends hold for a nonzero correlation between the exponent and the mean logarithm of a set of responses. The power of statistical tests of differences between mean intercepts also depends on the geometric mean of the stimuli. Power is reduced as the geometric mean deviates from one. Effects are illustrated with real data.     

Comparing Latent Means Without Mean Structure Models: A Projection-Based Approach

The conventional setup for multi-group structural equation modeling requires a stringent condition of cross-group equality of intercepts before mean comparison with latent variables can be conducted. This article proposes a new setup that allows mean comparison without the need to estimate any mean structural model. By projecting the observed sample means onto the space of the common scores and the space orthogonal to that of the common scores, the new setup allows identifying and estimating the means of the common and specific factors, although, without replicate measures, variances of specific factors cannot be distinguished from those of measurement errors. Under the new setup, testing cross-group mean differences of the common scores is done independently from that of the specific factors. Such independent testing eliminates the requirement for cross-group equality of intercepts by the conventional setup in order to test cross-group equality of means of latent variables using chi-square-difference statistics. The most appealing piece of the new setup is a validity index for mean differences, defined as the percentage of the sum of the squared observed mean differences that is due to that of the mean differences of the common scores. By analyzing real data with two groups, the new setup is shown to offer more information than what is obtained under the conventional setup.     

Dichotic listening performance to CVs between versus within groups

The present study is concerned with comparing group mean data between groups with individual performance within groups in dichotic listening (DL). It is argued that only comparing mean ear performance in dichotic listening between groups may obscure important individual differences within groups in DL performance. In the present study we compared between group vs. within group performance in four groups of subjects (male and female, right- and left-handers). The stimuli were 66 trials of consonant-vowel combinations with the six stop-consonants and the vowels a and u. The results showed a group mean right ear advantage for consonants in the two right-handed groups, and a left-ear advantage in the two let-handed groups. The analysis of the individual distributions within each group, however, showed clear differences between the male and female groups. Generally, though, only the male right-handed group revealed enough homogeneity within the group to warrant the conclusion that the group mean REA reflects a left hemisphere specialization for speech perception.     

潜变量交互效应建模: 告别均值结构

潜变量交互效应建模研究近年来有了长足的发展, 但模型中被认为不可缺少的均值结构往往让实际应用工作者却步。本文首先分析了潜变量交互效应模型中均值结构产生的根源; 然后讨论了指标变换与均值结构的关系; 接着提出了一个均值为零的潜变量交互结构, 所建立的模型不需要均值结构, 却不会改变主效应和交互效应等参数; 最后用模拟例子对无均值结构和有均值结构的两种模型的参数估计进行了比较, 结果符合理论预期, 困扰人们多年的均值结构问题从此可以终结。     

Clarifying the role of mean centring in multicollinearity of interaction effects

Moderated multiple regression (MMR) is frequently employed to analyse interaction effects between continuous predictor variables. The procedure of mean centring is commonly recommended to mitigate the potential threat of multicollinearity between predictor variables and the constructed cross-product term. Also, centring does typically provide more straightforward interpretation of the lower-order terms. This paper attempts to clarify two methodological issues of potential confusion. First, the positive and negative effects of mean centring on multicollinearity diagnostics are explored. It is illustrated that the mean centring method is, depending on the characteristics of the data, capable of either increasing or decreasing various measures of multicollinearity. Second, the exact reason why mean centring does not affect the detection of interaction effects is given. The explication shows the symmetrical influence of mean centring on the corrected sum of squares and variance inflation factor of the product variable while maintaining the equivalence between the two residual sums of squares for the regression of the product term on the two predictor variables. Thus the resulting test statistic remains unchanged regardless of the obvious modification of multicollinearity with mean centring. These findings provide a clear understanding and demonstration on the diverse impact of mean centring in MMR applications.     

暴发性1型糖尿病：一种不可忽视的重症糖尿病

暴发性1型糖尿病以起病急骤、代谢紊乱严重、胰酶升高并缺乏糖尿病相关抗体为特征。本文回顾分析我院收治的3例暴发性l型糖尿病的临床资料并结合文献与经典1型糖尿病进行对比复习,以提高对该病的认识。3例患者平均病程5．3天,入院平均血糖27．8mmol／L,平均糖化血红蛋白（HbAlC）6．8％,平均空腹C肽0．043ng／ml,平均餐后2hC肽0．04ng／ml,平均胰岛素使用剂量0．50U／（kg·d）。随访6个月HbAlC平均值为7．5％,胰岛8细胞功能无改善。暴发性1型糖尿病较经典1型糖尿病有更严重的胰岛素缺乏、代谢紊乱,更强烈的免疫反应,预后较差。     

Estimating the mean effect size in meta-analysis: Bias,precision, and mean squared error of different weighting methods

Although use of the standardized mean difference in meta-analysis is appealing for several reasons, there are some drawbacks. In this article, we focus on the following problem: that a precision-weighted mean of the observed effect sizes results in a biased estimate of the mean standardized mean difference. This bias is due to the fact that the weight given to an observed effect size depends on this observed effect size. In order to eliminate the bias, Hedges and Olkin (1985) proposed using the mean effect size estimate to calculate the weights. In the article, we propose a third alternative for calculating the weights: using empirical Bayes estimates of the effect sizes. In a simulation study, these three approaches are compared. The mean squared error (MSE) is used as the criterion by which to evaluate the resulting estimates of the mean effect size. For a meta-analytic dataset with a small number of studies, theMSE is usually smallest when the ordinary procedure is used, whereas for a moderate or large number of studies, the procedures yielding the best results are the empirical Bayes procedure and the procedure of Hedges and Olkin, respectively.     

Analysis of mean learning of normal participants on the Rey Auditory-Verbal Learning Test

Analysis of the mean performance of 58 groups of normal adults and children on the free-recall trials of the Rey Auditory-Verbal Learning Test shows that the mean auditory-verbal learning of each group is described by the function R1 + Sln(t), where R1 is a measure of the mean immediate memory span, S is the slope of the mean logarithmic learning curve, and ln(t) is the natural logarithm of the trial number t. The analysis also shows that R1 varies with age and other demographic factors, whereas S is almost a constant, and it yields equations for estimating the effect of these factors on R1. Potential use of these findings for assessment of auditory-verbal memory and learning in comparative clinical studies is discussed.     

A proof for Rhiel's range estimator of the coefficient of variation for skewed distributions

In this research study is proof that the coefficient of variation (CV(high-low)) calculated from the highest and lowest values in a set of data is applicable to specific skewed distributions with varying means and standard deviations. Earlier Rhiel provided values for d(n), the standardized mean range, and a(n), an adjustment for bias in the range estimator of micro. These values are used in estimating the coefficient of variation from the range for skewed distributions. The d(n) and an values were specified for specific skewed distributions with a fixed mean and standard deviation. In this proof it is shown that the d(n) and an values are applicable for the specific skewed distributions when the mean and standard deviation can take on differing values. This will give the researcher confidence in using this statistic for skewed distributions regardless of the mean and standard deviation.     

Centering predictor variables in cross-sectional multilevel models: a new look at an old issue

Appropriately centering Level 1 predictors is vital to the interpretation of intercept and slope parameters in multilevel models (MLMs). The issue of centering has been discussed in the literature, but it is still widely misunderstood. The purpose of this article is to provide a detailed overview of grand mean centering and group mean centering in the context of 2-level MLMs. The authors begin with a basic overview of centering and explore the differences between grand and group mean centering in the context of some prototypical research questions. Empirical analyses of artificial data sets are used to illustrate key points throughout. The article provides a number of practical recommendations designed to facilitate centering decisions in MLM applications.     

VEP latency and some properties of simple motor reaction-time distribution

Summary The median of simple motor reaction (RT) to a flash parallels the latencies of visually evoked potential (VEP) deflections if flash intensity is varied. However, mean and median reaction times are not equal because of the skewness of RT distribution. It therefore seemed plausible that the mean reaction time — intensity relationship would be steeper than that for VEP latency. Such divergence would account for the intensity-dependent motor component of RT revealed by other psychophysical studies. The latencies of VEP deflections were measured as a function of intensity and the results were compared with mean and median RTs. The difference between mean and median RT is constant and independent of flash intensity. Moreover, both values are parallel to VEP latency. The general pattern of results remains the same after a change in the distribution from which the foreperiod is sampled.     

企业员工行为中庸化的特征分析

本研究采用了问卷调查法,对苏州271名企业员工的行为中庸化的特征进行了研究。结果表明：（1）企业员工的行为,总体上是趋向于中庸的;（2）男性员工较女性员工在行为上更倾向于中庸;（3）教育水平高的员工较教育水平低的员工更倾向于中庸;（4）职务水平高的员工较职务水平低的员工更倾向于中庸;（5）企业性质不同、资本来源不同的企业员工,其行为中庸化水平不同。     

Cognitive Insight in Inpatients with Psychotic, Bipolar, and Major Depressive Disorders

The Beck Cognitive Insight Scale (BCIS; Beck, Baruch, Balter, Steer, & Warman, 2004) was administered to 42 (28%) inpatients with psychotic disorders, 52 (35%) with a bipolar disorder, and 56 (37%) with a major depressive disorder (MDD). The hypotheses were (a) that the mean level of cognitive insight in a psychotic or a bipolar disorder is lower than that in a MDD, (b) that the mean levels of cognitive insight in psychotic and bipolar disorders were comparable, and (c) that the mean BCIS index score for a bipolar disorder in which the most recent episode had been mania is lower than the mean BCIS index score for a bipolar disorder in which the most recent episode had been mixed or depressed. All three hypotheses were supported. The results were discussed as supporting cognitive insight as a psychological construct that varies predictably according to the nature of a psychiatric disorder.     

Imputation methods for missing data in educational diagnostic evaluation

In the diagnostic evaluation of educational systems, self-reports are commonly used to collect data, both cognitive and orectic. For various reasons, in these self-reports, some of the students' data are frequently missing. The main goal of this research is to compare the performance of different imputation methods for missing data in the context of the evaluation of educational systems. On an empirical database of 5,000 subjects, 72 conditions were simulated: three levels of missing data, three types of loss mechanisms, and eight methods of imputation. The levels of missing data were 5%, 10%, and 20%. The loss mechanisms were set at: Missing completely at random, moderately conditioned, and strongly conditioned. The eight imputation methods used were: listwise deletion, replacement by the mean of the scale, by the item mean, the subject mean, the corrected subject mean, multiple regression, and Expectation-Maximization (EM) algorithm, with and without auxiliary variables. The results indicate that the recovery of the data is more accurate when using an appropriate combination of different methods of recovering lost data. When a case is incomplete, the mean of the subject works very well, whereas for completely lost data, multiple imputation with the EM algorithm is recommended. The use of this combination is especially recommended when data loss is greater and its loss mechanism is more conditioned. Lastly, the results are discussed, and some future lines of research are analyzed.     

The consistency of presented personality: Additional evidence from aggregation

The present study investigated people's variability across situations by getting ratings of 66 subjects on 14 bipolar dimensions from at least eight interactants, chosen for their diversity. The intercorrelation of single ratings yielded a mean coefficient of .221. The correlation of single ratings with the aggregate of the other ratings for a dimension resulted in a mean coefficient of .388. The correlation of two sets of aggregated ratings gave a mean coefficient of .550, or .710 with application of the Spearman-Brown correction. Finally, computation of Cronbach's alpha gave a mean coefficient of .735. The results provide a further demonstration of the coherence that can be revealed by aggregation. Correlations of aggregated ratings on each of the 14 dimensions with extraversion ranged up to .668, and correlations with neuroticism ranged up to .410. The study suggests that there is a dispositionality in the characteristics people display, and that the emphasis on variability (e.g., Mischel, 1968; Mischel & Peake, 1982) should be tempered.     

The validity of the Comprehensive Test of Nonverbal Intelligence as a measure of fluid intelligence

The current investigation examined the validity of the Comprehensive Test of Nonverbal Intelligence (CTONI), an intelligence test that is purported to measure fluid intelligence. The CTONI was evaluated in comparison with the Kaufman Adolescent and Adult Intelligence Test (KAIT), an established measure of fluid and crystallized intelligence. Ninety-seven adults were administered these instruments in counterbalanced order. Results indicated that the sample's mean CTONI Nonverbal IQ (NIQ) deviated significantly from the mean KAIT Crystallized, Fluid, and Composite IQs. The CTONI mean NIQ underestimated KAIT Fluid and Composite IQs when individual participants were subdivided into existing KAIT ability categories and mean score comparisons were made. Results also indicated that the CTONI NIQ correlated strongly and positively with the KAIT Composite and Fluid IQs. Furthermore, the CTONI Geometric NIQ scale clearly demonstrated discriminant and convergent validity, whereas, the CTONI Pictorial NIQ (PNIQ) did not.     

Beyond shared perceptions of trust and monitoring in teams: implications of asymmetry and dissensus

Past research has implicitly assumed that only mean levels of trust and monitoring in teams are critical for explaining their interrelations and their relationships with team performance. In this article, the authors argue that it is equally important to consider the dispersion in trust and monitoring that exists within teams. The authors introduce "trust asymmetry" and "monitoring dissensus" as critical dispersion properties of trust and monitoring and hypothesize that these moderate the relationships between mean monitoring, mean trust, and team performance. Data from a cross-lagged panel study and a partially lagged study support the hypotheses. The first study also offered support for an integrative model that includes mean and dispersion levels of both trust and monitoring. Overall, the studies provide a comprehensive and clear picture of how trust and monitoring emerge and function at the team level via mean and dispersion.