免除伦理审查制度适法性与可操作性探讨

结合我国现行法律和基本伦理原则,深入分析了免除伦理审查的前置条件和适用情形在适法性与可操作性上可能存在的问题,并在此基础上提出了可行性的建议：第一,明确监管范围,免除伦理审查是一种特殊的审查方式,而非不进行伦理审查;第二,全面评估风险,对研究的风险判断不仅要考虑因研究给个人带来的生理风险,还应考虑其心理、经济、社会以及法律等方面的风险,尤其是对最小风险应明确界定;第三,界定前置条件中的具体概念,以及在此基础上适用情形的判断,制定具体、合理、合法的实施细则,为免除伦理审查的实施提供参考。

     

Social networks with two sets of actors

Traditional network research analyzes relational ties within a single group of actors: the models presented in this paper involve relational ties exist beteen two distinct sets of actors. Statistical models for traditional networks in which relations are measured within a group simplify when modeling unidirectional relations measured between groups. The traditional paradigm results in a one-mode socionatrix; the network paradigm considered in this paper results in a two-mode socionatrix; A statistical model is presented, illustrated on a sample data set, and compared to its traditional counterpart. Extensions are discussed, including those that model multivariate relations simultaneously, and those that allow for the inclustion of attributes of the individuals in the group.We thank the Editor and two anonymous reviewers for their helpful comments. We are also grateful to George Barnett for allowing us to analyze his data.     

认知诊断缺失数据处理方法的比较：零替换、多重插补与极大似然估计法

数据缺失在测验中经常发生, 认知诊断评估也不例外, 数据缺失会导致诊断结果的偏差。首先, 通过模拟研究在多种实验条件下比较了常用的缺失数据处理方法。结果表明：(1)缺失数据导致估计精确性下降, 随着人数与题目数量减少、缺失率增大、题目质量降低, 所有方法的PCCR均下降, Bias绝对值和RMSE均上升。(2)估计题目参数时, EM法表现最好, 其次是MI, FIML和ZR法表现不稳定。(3)估计被试知识状态时, EM和FIML表现最好, MI和ZR表现不稳定。其次, 在PISA2015实证数据中进一步探索了不同方法的表现。综合模拟和实证研究结果, 推荐选用EM或FIML法进行缺失数据处理。     

医疗机器人的伦理风险与治理探析——基于“医−患−机”分析框架

基于“医−患−机”分析框架,医疗机器人的不断发展面临主体资质复杂、责任认定困难等责任伦理风险,医患关系重构、医患信任危机等医患伦理风险,数据质量与数据隐私等数据伦理风险,算法安全与算法偏见等算法伦理风险以及医疗资源分配正义风险。医疗机器人的伦理治理要以医学伦理和机器人伦理准则为依据,建立多元伦理治理体制,推动学术共同体的构建,探索自愿型、调节型与管制型等伦理治理工具的组合运用,加快医疗机器人伦理治理的法治化发展。

     

Psychometric properties and factor structure of the Fear Questionnaire phobia subscale items in two normative samples

Normative data for the Fear Questionnaire (Marks & Mathews, 1979), a popular self-report instrument measuring phobic concerns, were collected from both a community and a collegiate sample. The covariation and internal consistency of the blood-injury phobia (BI), social phobia (SO), and agoraphobia (AG) subscales were assessed in each sample, and the factor structure of the items from these three subscales was examined. Results indicated that, in general, community subjects reported more phobic concerns than did collegiate subjects, and females reported greater phobic concerns than did males. Results from confirmatory factor analyses suggest that the three factors of BI, SO, and AG did not emerge from either data set. Follow-up exploratory factor analyses did identify the general factors of blood-injury phobia and agoraphobia. Normative data from the present study are compared to those obtained previously, and directions for future research are provided.     

间隔时间及记忆负荷对信息缺失错误记忆的影响

现场中的信息缺失会影响人类对事件的记忆,这对证人证言研究是非常重要的,但以往对之却鲜有研究.本研究以大学生为被试,运用信息缺失范式,采用视频录像材料,通过2个实验探讨了间隔时间和记忆负荷对错误记忆的影响.结果表明:(1)间隔时间没有影响真实记忆和错误记忆,但信心水平却随着间隔时间的延长而变化;(2)记忆负荷高低没有影响真实记忆却影响了错误记忆,在关键信息呈现条件下,降低记忆负荷可以减少错误记忆的发生;(3)信息性质会影响人们的记忆,关键信息呈现条件下的错误记忆和真实记忆均高于关键信息缺失的条件.     

Hierarchical models for relational event sequences

Interaction within small groups can often be represented as a sequence of events, each event involving a sender and a recipient. Recent methods for modeling network data in continuous time model the rate at which individuals interact conditioned on the previous history of events as well as actor covariates. We present a hierarchical extension for modeling multiple such sequences, facilitating inferences about event-level dynamics and their variation across sequences. The hierarchical approach allows one to share information across sequences in a principled manner—we illustrate the efficacy of such sharing through a set of prediction experiments. After discussing methods for adequacy checking and model selection for this class of models, the method is illustrated with an analysis of high school classroom dynamics from 297 sessions.     

A Test of Order-Constrained Hypotheses for Circular Data With Applications to Human Movement Science

Researchers studying the movements of the human body often encounter data measured in angles (e.g., angular displacements of joints). The evaluation of these circular data requires special statistical methods. The authors introduce a new test for the analysis of order-constrained hypotheses for circular data. Through this test, researchers can evaluate their expectations regarding the outcome of an experiment directly by representing their ideas in the form of a hypothesis containing inequality constraints. The resulting data analysis is generally more powerful than one using standard null hypothesis testing. Two examples of circular data from human movement science are presented to illustrate the use of the test. Results from a simulation study show that the test performs well.     

Evaluating Structural Equation Models for Categorical Outcomes: A New Test Statistic and a Practical Challenge of Interpretation

This research is concerned with two topics in assessing model fit for categorical data analysis. The first topic involves the application of a limited-information overall test, introduced in the item response theory literature, to structural equation modeling (SEM) of categorical outcome variables. Most popular SEM test statistics assess how well the model reproduces estimated polychoric correlations. In contrast, limited-information test statistics assess how well the underlying categorical data are reproduced. Here, the recently introduced C₂ statistic of Cai and Monroe (2014) is applied. The second topic concerns how the root mean square error of approximation (RMSEA) fit index can be affected by the number of categories in the outcome variable. This relationship creates challenges for interpreting RMSEA. While the two topics initially appear unrelated, they may conveniently be studied in tandem since RMSEA is based on an overall test statistic, such as C₂. The results are illustrated with an empirical application to data from a large-scale educational survey.