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.     

Estimating Incremental Validity Under Missing Data

A common form of missing data is caused by selection on an observed variable (e.g., Z). If the selection variable was measured and is available, the data are regarded as missing at random (MAR). Selection biases correlation, reliability, and effect size estimates when these estimates are computed on listwise deleted (LD) data sets. On the other hand, maximum likelihood (ML) estimates are generally unbiased and outperform LD in most situations, at least when the data are MAR. The exception is when we estimate the partial correlation. In this situation, LD estimates are unbiased when the cause of missingness is partialled out. In other words, there is no advantage of ML estimates over LD estimates in this situation. We demonstrate that under a MAR condition, even ML estimates may become biased, depending on how partial correlations are computed. Finally, we conclude with recommendations about how future researchers might estimate partial correlations even when the cause of missingness is unknown and, perhaps, unknowable.     

计划缺失设计——通过有意缺失让研究更高效

缺失值是社会科学研究中非常普遍的现象。全息极大似然估计和多重插补是目前处理缺失值最有效的方法。计划缺失设计利用特殊的实验设计有意产生缺失值, 再用现代的缺失值处理方法来完成统计分析, 获得无偏的统计结果。计划缺失设计可用于横断面调查减少(或增加)问卷长度和纵向调查减少测量次数, 也可用于提高测量有效性。常用的计划缺失设计有三式设计和两种方法测量。     

Nihilism: Beyond Optimism and Pessimism

Studies in Philosophy and Education - Is the youth culture, or more precisely aparticular kind of it, to be characterized as “nihilistic”? And is this a threat or ablessing for...     

Self-Transcendence: Integrating Ends and Means in Value Counseling

Pastoral counseling is distinguished from secular counseling by “limit experiences.” These are experiences that disclose the fullness of self-transcendence—for Christians, a personal relationship with God. But the radical drive of the human spirit for self-transcendence unifies every dimension of the developing person. This drive thus forms the basis of a fundamental continuity between pastoral and secular counseling in their directions and methods, despite clear differences in boundaries, categories, and languages.     

追踪研究中缺失数据处理方法及应用现状分析

追踪研究中普遍存在缺失数据, 缺失数据处理方法的选择影响统计推断的精度及研究结果的有效性。首先, 阐述缺失机制及判断方法, 比较追踪研究中主要的缺失数据处理方法的特点、及实际应用中的缺失处理方法的选择和软件实现。其次, 对国内心理学中92篇追踪研究文献进行分析, 发现有59篇(64.13%)报告不同程度缺失, 其中仅39篇报告了处理方法且均为删除法。未来研究应深入探讨现有缺失数据处理方法的有效性, 进一步规范应用研究中缺失数据的处理。     

Epistemic Means and Ends: In Defense of Some Sartwellian Insights

The question of what means-and-ends structure our epistemic endeavors have is an important issue in recent epistemology, and is fundamental for understanding epistemic matters in principle. Crispin Sartwell has proposed arguments for the view that knowledge is our only ultimate goal, and justification is no part of it. An important argument is his instrumentality argument which is concerned with the conditions under which something could belong to our ultimate epistemic goal. Recently, this argument has been reconstructed and criticized by Pierre Le Morvan in a clear and helpful way. It will be shown, however, that Le Morvan’s criticism is not adequate, since it misconstrues the real instrumentality argument that can be found in Sartwell’s writings.     

Of Means and Ends: Religion and the Search for Significance

This article attempts to depolarize the concepts of means and ends in the psychology of religion. It is argued that everyone uses his or her religion. However, religion can be used in constructive as well as destructive ways. The critical question is not whether religion is lived or used, as Allport suggested, but how religion is used and to what ends. Thinking about religion as means and ends rather than means or ends offers a framework for organizing the richly diverse forms and functions of religious life, spiritual as well as nonspiritual. It provides a way to conceptualize and study the widely used but poorly defined notion of religious orientation. It also offers a way to evaluate the efficacy of religion in living.     

Reasons for Having Children: Ends, Means and 'Family Values'

This essay suggests some links between concern about the decline of 'the family', or of 'family values', the use of reproductive technology, and the claim that some people have children for the 'wrong reasons'. It is argued that where conceiving and bringing a child to term is a matter of choice, a person must have a reason or reasons for doing so and further, that those reasons are of moral significance. By appealing to Kant's Categorical Imperative: 'Act in such a way that you always treat humanity … never simply as a means, but always at the same time as an end', a distinction is made between morally desirable and morally undesirable reasons, on the grounds of the extent to which the parent or parents will be able or likely to treat the child as an end in herself. In conclusion it is argued that whilst 'the family'is vital to the health of children, and to the health of society, it is not so much the form that the family takes that is significant, but the extent to which it allows for the development and maintainance of a certain sort of relationship.     

Measuring Creativity with Planned Missing Data

This paper introduces a method for the assessment of creativity that relies on creativity tasks, a subjective evaluation procedure, and a planned missing data design that offers a drastic reduction in the overall implementation costs (administration time and scoring procedure). This method was tested on a sample of 149 people, using three creativity tasks as a basis. Participants were instructed to produce several ideas in each task and then to select what they considered to be their best two ideas (i.e., “Top 2” procedure; Silvia, Winterstein, Willse, Barona, et al., Psychology of Aesthetics, Creativity, and the Arts, 2 , 2008 and 68). These ideas were then evaluated by a panel of peers and experts. Creativity ratings were analyzed with structural equations; measurement models were estimated for each task and correlations between factor-scores across the three tasks were investigated. Further insights regarding validity are provided through systematic investigation of the relationship between fluency scores, creativity ratings, intelligence tasks, self-reported idea generation abilities, and creative activities and achievements. Overall, the results support the viability of this new approach, providing evidence of convergent and discriminant validity. They are discussed in relation to past research and avenues for further extension are proposed.     

A Comparison of Imputation Strategies for Ordinal Missing Data on Likert Scale Variables

This article compares a variety of imputation strategies for ordinal missing data on Likert scale variables (number of categories = 2, 3, 5, or 7) in recovering reliability coefficients, mean scale scores, and regression coefficients of predicting one scale score from another. The examined strategies include imputing using normal data models with naïve rounding/without rounding, using latent variable models, and using categorical data models such as discriminant analysis and binary logistic regression (for dichotomous data only), multinomial and proportional odds logistic regression (for polytomous data only). The result suggests that both the normal model approach without rounding and the latent variable model approach perform well for either dichotomous or polytomous data regardless of sample size, missing data proportion, and asymmetry of item distributions. The discriminant analysis approach also performs well for dichotomous data. Naïvely rounding normal imputations or using logistic regression models to impute ordinal data are not recommended as they can potentially lead to substantial bias in all or some of the parameters.     

缺失数据处理的期望-极大化算法与马尔可夫蒙特卡洛方法

缺失数据普遍存在于心理学研究中, 影响着统计推断。极大似然估计(MLE)与基于贝叶斯的多重借补(MI)是处理缺失数据的两类重要方法。期望-极大化算法(EM)是寻求MLE的一种强有力的方法。马尔可夫蒙特卡洛方法(MCMC)可以相对简易地实现MI, 而且可以适用于复杂情况下的缺失数据处理。结合研究的需要讨论了实现这两类方法的适用软件。     

Addressing Item-Level Missing Data: A Comparison of Proration and Full Information Maximum Likelihood Estimation

Often when participants have missing scores on one or more of the items comprising a scale, researchers compute prorated scale scores by averaging the available items. Methodologists have cautioned that proration may make strict assumptions about the mean and covariance structures of the items comprising the scale (Schafer &; Graham, 2002 Schafer, J.L., &; Graham, J.W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]; Graham, 2009 Graham, J.W. (2009). Missing data analysis: Making it work in the real world. Annual Review of Psychology, 60, 549–576.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]; Enders, 2010 Enders, C.K. (2010). Applied missing data analysis. New York, NY: Guilford Press. [Google Scholar]). We investigated proration empirically and found that it resulted in bias even under a missing completely at random (MCAR) mechanism. To encourage researchers to forgo proration, we describe a full information maximum likelihood (FIML) approach to item-level missing data handling that mitigates the loss in power due to missing scale scores and utilizes the available item-level data without altering the substantive analysis. Specifically, we propose treating the scale score as missing whenever one or more of the items are missing and incorporating items as auxiliary variables. Our simulations suggest that item-level missing data handling drastically increases power relative to scale-level missing data handling. These results have important practical implications, especially when recruiting more participants is prohibitively difficult or expensive. Finally, we illustrate the proposed method with data from an online chronic pain management program.     

Obstetric Ultrasound and the Technological Mediation of Morality: A Postphenomenological Analysis

This article analyzes the moral relevance of technological artifacts and its possible role in ethical theory, by taking the postphenomenological approach that has developed around the work of Don Ihde into the domain of ethics. By elaborating a postphenomenological analysis of the mediating role of ultrasound in moral decisions about abortion, the article argues that technologies embody morality and help to constitute moral subjectivity. This technological mediation of the moral subject is subsequently addressed in terms of Michel Foucault’s ethical position, in which ethics is about actively co-shaping one’s moral subjectivity. Integrating Foucauldian ethics and postphenomenology, the article argues that the technological mediation of moral subjectivity should be at the heart of an ethical approach that takes the moral dimensions of technology seriously.

2PL模型的两种马尔可夫蒙特卡洛缺失数据处理方法比较

马尔科夫蒙特卡洛（MCMC）是项目反应理论中处理缺失数据的一种典型方法。文章通过模拟研究比较了在不同被试人数,项目数,缺失比例下两种MCMC方法（M-H within Gibbs和DA-T Gibbs）参数估计的精确性,并结合了实证研究。研究结果表明,两种方法是有差异的,项目参数估计均受被试人数影响很大,受缺失比例影响相对更小。在样本较大缺失比例较小时,M-H within Gibbs参数估计的均方误差（RMSE）相对略小,随着样本数的减少或缺失比例的增加,DA-T Gibbs方法逐渐优于M-H within Gibbs方法     

概化理论缺失数据方差分量估计

各种心理调查、心理实验中, 数据的缺失随处可见。由于数据缺失, 给概化理论分析非平衡数据的方差分量带来一系列问题。基于概化理论框架下, 运用Matlab 7.0软件, 自编程序模拟产生随机双面交叉设计p×i×r缺失数据, 比较和探讨公式法、REML法、拆分法和MCMC法在估计各个方差分量上的性能优劣。结果表明：(1) MCMC方法估计随机双面交叉设计p×i×r缺失数据方差分量, 较其它3种方法表现出更强的优势; (2) 题目和评分者是缺失数据方差分量估计重要的影响因素。