Measuring Moral Progress

The study provides an in-depth analysis of two young adult subjects from a longitudinal study who underwent successive and significant developmental changes. Their developmental patterns, however, are only revealed by a new conception of moral stages, which is both more comprehensive and more detailed than Kohlberg’s original approach. In particular, the suggested alternative taxonomy neatly accommodates what appears as developmental anomalies in the Kohlbergian frame of reference. What is more, apart from merely matching with the observed data, the new theory also explains why the subjects developed the way they did, since it reveals the inherent cognitive conflicts at each stage and how these are resolved at the following one. Although the theory stands against the Kohlberg theory as it is, it may be understood as an extension and further development of the latter, in the sense that Kohlbergian stages are differentiated, supplemented, and theoretically substantiated within the new framework.

A class of multidimensional IRT models for testing unidimensionality and clustering items

We illustrate a class of multidimensional item response theory models in which the items are allowed to have different discriminating power and the latent traits are represented through a vector having a discrete distribution. We also show how the hypothesis of unidimensionality may be tested against a specific bidimensional alternative by using a likelihood ratio statistic between two nested models in this class. For this aim, we also derive an asymptotically equivalent Wald test statistic which is faster to compute. Moreover, we propose a hierarchical clustering algorithm which can be used, when the dimensionality of the latent structure is completely unknown, for dividing items into groups referred to different latent traits. The approach is illustrated through a simulation study and an application to a dataset collected within the National Assessment of Educational Progress, 1996. The author would like to thank the Editor, an Associate Editor and three anonymous referees for stimulating comments. I also thank L. Scaccia, F. Pennoni and M. Lupparelli for having done part of the simulations.     

A Statistical Interpretive Method for Neuropsychological Test Data

The accurate interpretation of large numbers of neuropsychological tests within a flexible battery approach is a difficult and sometimes controversial process. We present a statistically based method of interpretation (Rohling's Interpretive Method or RIM) and evaluation of neuropsychological data that allows for varying numbers of tests along a varying number of cognitive domains, yet remains psychometrically based. This method requires informed clinical judgment in that the level of confidence for tests, cognitive domains, and global indices are used as the backdrop for interpretive decisions. Specific procedures for use are presented in a systematic, detailed fashion to allow the interested reader to replicate the method. Two case examples are presented: a straightforward case of cerebrovascular insult and a more complicated case of mixed etiology. Examples include a variety of different neuropsychological tests commonly used in a flexible battery approach. A discussion of the practicality, ease of use, and potential limitations of this method are further presented.     

A method for analyzing changes in response efficiency.

Although experimental effects typically are evaluated by summarizing levels of responding across time (e.g., calculating the mean levels of problem behavior during 10‐min sessions), these data summaries may obscure important mechanisms that may be responsible for changes in responding. A case study is reported to illustrate alternative methods of data analysis when decreasing trends in responding may be due to increases in response efficiency.     

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。     

Sensitive Topics,Missing Data,and Refusal in Social Network Studies: An Ethical Examination

We describe our ethics‐driven process of addressing missing data within a social network study about accountability for racism, classism, sexism, heterosexism, cis‐sexism, ableism, and other forms of oppression among social justice union organizers. During data collection, some would‐be participants did not return emails and others explicitly refused to engage in the research. All refusals came from women of color. We faced an ethical dilemma: Should we continue to seek participation from those who had not yet responded, with the hopes of recruiting more women of color from within the network so their perspectives would not be tokenized? Or, should we stop asking those who had been contacted multiple times, which would compromise the social network data and analysis? We delineate ways in which current discussions of the ethics of social network studies fell short, given our framework and our community psychology (CP ) values. We outline literature that was helpful in thinking through this challenge; we looked outside of CP to the decolonization literature on refusal. Lessons learned include listening for the possible meanings of refusals and considering the level of engagement and the labor required of participants when designing research studies.     

数据权属与规制探讨

数据可分为原生数据与衍生数据。原生数据视来源不同分属国家、集体或个人。数据处理而形成的衍生数据往往涉及多方利益,形成“利益光谱”,对应多方权利主体。基于价值优先次序、权利位阶规则等,数据利益的“两头强化,多方平衡”,是我国法律数据确权和规制的指导思想。“两头强化”是指法律强化对位于“利益光谱”两端的国家利益与个人权益的保护,“多方平衡”指的是多方主体数据权益的平衡。数据规制的“硬法”进路为：明确法律概念,分析“利益光谱”,确定利益归属,权衡优先次序,平衡多方利益,搭建规制框架,制定具体规则。

     

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。