信度系数与观测分数和潜在特质的相关比

在经典真分数模型中,信度系数R=D(T)/D(X)。通常认为,信度系数与项目反应理论没有什么联系。事实上,信度系数恰好等于考生观测分数与潜在特质分数的非线性相关比η_(xθ)~2=1-MD(x|θ)/D(X),据此我们得出估计信度系数的一种新途径,同时讨论了x、θ的相关系数与相关比η_(xθ)~2的关系。     

Individual differences in harm-related moral values are associated with functional integration of large-scale brain networks of emotional regulation

Emotions affects moral judgements, and controlled cognitive processes regulate those emotional responses during moral decision making. However, the neurobiological basis of this interaction is unclear. We used a graph theory measurement called participation coefficient (‘PC’) to quantify the resting-state functional connectivity within and between four meta-analytic groupings (MAGs) associated with emotion generation and regulation, to test whether that measurement predicts individual differences in moral foundations-based values. We found that the PC of one of the MAGs (MAG2) was positively correlated with one of the five recognized moral foundations–the one based on harm avoidance. We also found that increased inter-module connectivity between the ventromedial prefrontal cortex, dorsolateral prefrontal cortex and middle temporal gyrus with other nodes in the four MAGs was likewise associated with higher endorsement of the Harm foundation. These results suggest that individuals' sensitivity to harm is associated with functional integration of large-scale brain networks of emotional regulation. These findings add to our knowledge of how individual variations in our moral values could be reflected by intrinsic brain network organization and deepen our understanding of the relationship between emotion and cognition during evaluations of moral values.     

Effect sizes in ANCOVA and difference-in-differences designs

It is common practice in both randomized and quasi-experiments to adjust for baseline characteristics when estimating the average effect of an intervention. The inclusion of a pre-test, for example, can reduce both the standard error of this estimate and—in non-randomized designs—its bias. At the same time, it is also standard to report the effect of an intervention in standardized effect size units, thereby making it comparable to other interventions and studies. Curiously, the estimation of this effect size, including covariate adjustment, has received little attention. In this article, we provide a framework for defining effect sizes in designs with a pre-test (e.g., difference-in-differences and analysis of covariance) and propose estimators of those effect sizes. The estimators and approximations to their sampling distributions are evaluated using a simulation study and then demonstrated using an example from published data.     

急性心肌梗死患者小动脉弹性指数水平与各项危险因素的关系

探讨急性心肌梗死（AMI）患者小动脉弹性指数（C2）水平与各项风险因素的关系。纳入我院心血管内科于2010年1月～2013年7月间收治的AMI患者,并纳入同期入院的不稳定心绞痛（UA）患者作为对照组,收集相关临床资料,比较不同C2水平与相关指标的关联性发现：C2等11项危险因素存在显著差异,经多因素Logistic回归...     

2001年～2010年新疆13个地州市卫生资源配置公平性分析

基于洛伦兹曲线和基尼系数视角,对2001年～2010年新疆13个地州市卫生资源配置公平性进行分析,发现新疆13个地州市卫生技术人员和医生的配置大多数年份处于不公平状态,而病床的配置大多数年份处于比较公平状态,建议从卫生投入、政策倾斜及卫生人员培训等角度协调新疆卫生资源的配置.     

预测视角下双因子模型与高阶因子模型的一般性模拟比较

高阶因子模型本质上是一种特殊的双因子模型, 应用中却常被当做双因子模型的竞争模型。已有研究以满足比例约束的双因子模型(此时等价于一个高阶因子模型)为真实测量模型产生模拟数据, 比较了用双因子模型和高阶因子模型作为测量模型的预测效果。本文使用不满足比例约束的双因子模型(此时不与任何高阶因子模型等价)为真实测量模型产生模拟数据进行比较, 所得结果与满足比例约束的双因子模型的结果有很大差别, 双因子模型结构系数的相对偏差较小、检验力较高, 但第Ⅰ类错误率略高。结论是, 在比例约束条件成立时可以使用高阶因子模型, 否则, 从统计角度看, 一般情况下使用双因子模型进行预测比较好。     

On Association Coefficients for 2×2 Tables and Properties That Do Not Depend on the Marginal Distributions

We discuss properties that association coefficients may have in general, e.g., zero value under statistical independence, and we examine coefficients for 2×2 tables with respect to these properties. Furthermore, we study a family of coefficients that are linear transformations of the observed proportion of agreement given the marginal probabilities. This family includes the phi coefficient and Cohen’s kappa. The main result is that the linear transformations that set the value under independence at zero and the maximum value at unity, transform all coefficients in this family into the same underlying coefficient. This coefficient happens to be Loevinger’s H.     

A generalization of coefficient alpha

It is well known that coefficient alpha can be used to estimate the reliability of a test even when the test is split into several parts. It is also known that alpha can severely underestimate test reliability when the several parts have an unequal number of items. A gernalization of alpha,β _k, is proposed to correct this defect. Several properties ofβ _k are also presented. The author gratefully acknowledges the assistance of Dr. Leonard Feldt for reviewing an earlier draft of this paper, and Ms. Rita Karwacki Bode and Mr. Dave Mansell for the analysis of the experimental data reported here. The comments of an unknown referee which contributed substantially to the clarity of the presentation are also gratefully acknowledged.     

Psychometric properties of the Danish MCMI-I translation

A translation of the MCMI-I has been in use in Denmark for some years. An untested assumption in the interpretation of the pattern of test results is that the psychometric characteristics of the Danish and American versions are similar. The purpose of this study was to evaluate the psychometric properties of the questionnaire by using traditional psychometric analysis techniques on the results of a sample consisting of 423 patients and 179 normal controls. Coefficient alpha was calculated for the 20 clinical subscales of the test and the Danish results were strikingly similar to the original coefficients reported by Millon. Furthermore, factor analysis of the subscales showed a factor structure very similar to American findings, and it is concluded that the psychometric properties of the Danish MCMI are not significantly different from the original.     

Association coefficients of identity and proportionality for metric scales

Zegers' (1986) chance-corrected coefficients of association are derived by alternative methods. A different definition of chance correction is used. It is shown that our correction and that of Zegers are identical for large samples. Three possible assumptions for the derivation of metric coefficients are examined. The first, variable reflection, formulated by Zegers and ten Berge (1985), leads to coefficients that require chance-correction. Two other assumptions, zero covariance and covariance reflection, are proposed and it is shown that the latter two assumptions lead directly to coefficients of identity and proportionality that do not require chance correction (i.e., are identical to the Zegers, 1986, corrected coefficients).We are indebted to Robyn M. Dawes, Carnegie-Mellon University, for stimulating our interest in this project, and for helpful suggestions.