Assessing the predictive value of a binary surrogate for a binary true endpoint based on the minimum probability of a prediction error

The individual causal association (ICA) has recently been introduced as a metric of surrogacy in a causal‐inference framework. The ICA is defined on the unit interval and quantifies the association between the individual causal effect on the surrogate (ΔS) and true (ΔT) endpoint. In addition, the ICA offers a general assessment of the surrogate predictive value, taking value 1 when there is a deterministic relationship between ΔT and ΔS, and value 0 when both causal effects are independent. However, when one moves away from the previous two extreme scenarios, the interpretation of the ICA becomes challenging. In the present work, a new metric of surrogacy, the minimum probability of a prediction error (PPE), is introduced when both endpoints are binary, ie, the probability of erroneously predicting the value of ΔT using ΔS. Although the PPE has a more straightforward interpretation than the ICA, its magnitude is bounded above by a quantity that depends on the true endpoint. For this reason, the reduction in prediction error (RPE) attributed to the surrogate is defined. The RPE always lies in the unit interval, taking value 1 if prediction is perfect and 0 if ΔS conveys no information on ΔT. The methodology is illustrated using data from two clinical trials and a user‐friendly R package Surrogate is provided to carry out the validation exercise.     

One size fits all? The social construction of dis-employ-abled women

This article is based on an evaluation of a labour-market training programme for women with ‘mental health problems’ in a social workplace in Belgium. The research team explored the retrospective insider perspectives on the work aspirations of the women involved in the programme to identify critical dynamics in their high drop-out from the social workplace. The central findings provide evidence of a prevalent one-size-fits-all discourse in these practices wherein complex and interrelated processes of discrimination take place that are based on both disability and gender. The findings demonstrate that the social workplace functions as a male bastion, in which the oversized overalls that women are forced to wear are symbolically relevant. In conclusion, we discuss and challenge the dominance of the neo-liberal norm of economic productivity and employability.     

Clustering in dividends: Do managers rely on cognitive reference points?

Prior studies (see e.g. [Rosch, E. (1975). Cognitive reference points. Cognitive Psychology, 7, 532–547]) indicate that multiples of ten serve as cognitive reference points with a view to perceiving and evaluating numbers. In order to explore whether managers set dividends per share (henceforth DPS) at or just above a cognitive reference point, we perform a digital analysis on US firms’ DPS for the period 1995–2004. That is, based on the theory of cognitive reference points, DPS of $2.00 will be viewed as being abnormally larger than DPS of $1.99, whereas the actual difference only amounts to a marginal $0.01. Results presented in this paper indicate that managers fall back on cognitive reference points when they set DPS, which shows in significantly more (fewer) zeroes (large digits) in the second-from-the-left position of DPS than would normally be expected. Overall, results presented in this paper tally with prior findings on odd-ending prices and price clustering documented in related disciplines.     

Fast two-stage estimator for clustered count data with overdispersion

Clustered count data are commonly analysed by the generalized linear mixed model (GLMM). Here, the correlation due to clustering and some overdispersion is captured by the inclusion of cluster-specific normally distributed random effects. Often, the model does not capture the variability completely. Therefore, the GLMM can be extended by including a set of gamma random effects. Routinely, the GLMM is fitted by maximizing the marginal likelihood. However, this process is computationally intensive. Although feasible with medium to large data, it can be too time-consuming or computationally intractable with very large data. Therefore, a fast two-stage estimator for correlated, overdispersed count data is proposed. It is rooted in the split-sample methodology. Based on a simulation study, it shows good statistical properties. Furthermore, it is computationally much faster than the full maximum likelihood estimator. The approach is illustrated using a large dataset belonging to a network of Belgian general practices.     

Learning to make sense: interdisciplinary perspectives on sensory education and embodied enculturation

ABSTRACT

In this introductory essay we examine through a ‘temporally inflected lens’ some of the complex entanglements of learning, senses, and sense making; body-sensory experience and practice; and culture and society. We thereby aim to bring into dialogue inter-/multisensorial approaches to education as a project and praxis and processes of ‘enculturation’, which have always, in one way or the other, involved ‘embodied’ learning (and imaginaries thereof), rather than mere ‘mental processing’. We first situate the ‘turn’ to the senses, across a range of disciplinary fields, brought on by a growing interest in ‘modes of meaning-making’, including the visual, aural, audio-visual, material, bodily, and spatial. Secondly, we investigate the explanatory potential of enculturation and embodiment as seemingly entangled notions. From this, we derive the concept of ‘embodied enculturation’ for the study of situated, historical entanglements of sensory learning and education. We link this proposed research paradigm to incisive scholarship on ‘cultural learning’ through sensorial lenses, after which we tease out six key questions or concerns emerging from a review of relevant, recent research. These key concerns help to contextualize state-of-the-art ‘sensuous education scholarship’ introduced in the final section of the article and elaborated further in the ensuing contributions to this special issue.     

Turning a Blind Eye? Punishment of Friends and Unfamiliar Peers After Observed Exclusion in Adolescence

In order to decrease the occurrence of social exclusion in adolescence, we need to better understand how adolescents perceive and behave toward peers involved in exclusion. We examined the role of friendships in treatment of perpetrators and victims of social exclusion. Eighty‐nine participants (aged 9–16) observed exclusion of an unfamiliar peer (victim) by their best friend and another unfamiliar peer. Subsequently, participants could give up valuable coins to altruistically punish or help peers. Results showed that participants altruistically compensated victims and punished unfamiliar excluders, but refrained from punishing their friends. Our findings show that friendship with excluders modulates altruistic punishment of peers and provide mechanistic insight into how friendships may influence treatment of peers involved in social exclusion during adolescence.     

联盟组合多样性及其与绩效维度的关系

基于480家机构的以自我为中心的网络数据,分析了联盟组合多样性和财务绩效、激进式创新绩效、渐进式创新绩效等三个重要绩效维度之间的关系.其中,联盟组合多样性与财务绩效负相关;而联盟组合多样性与激进式创新绩效呈现倒U形关系;联盟组合多样性与渐进式创新绩效呈现递减收益正相关.结果表明,管理者应该意识到联盟组合多样性的可能的消极影响,并且意识到不同水平的联盟组合多样性是最有益的.     

Data Envelopment Analysis for Composite Indicators: A Multiple Layer Model

The development of a composite indicator (CI) over a set of individual indicators is worthwhile in case the methodological aggregation process is sound and the results are clear. It can then be used as a powerful tool for performance evaluation, benchmarking, and decision making. In this respect, data envelopment analysis (DEA), as a self appraisal technique, has recently received considerable attention in the construction of CIs for policy analysis and public communication. However, due to the ever increasing complexity of numerous performance evaluation problems, more and more potential indicators might be developed to represent an evaluation activity in a more comprehensive way. These indicators might also belong to different categories and further be linked to one another constituting a multilayer hierarchical structure. Simply treating all the indicators to be in the same layer as is the case in the basic DEA model thereby ignores the information on their hierarchical structure, and further leads up to weak discriminating power and unrealistic weight allocations. To overcome this limitation, a multiple layer DEA-based CI model is developed in this study to embody a hierarchical structure of indicators in the DEA framework, and both its primal and dual form are realized. The proposed model is illustrated by constructing a composite road safety performance index for a set of European countries.     

The effect of personalization on response rates and data quality in web surveys

Personalizing correspondence has often shown to significantly increase survey response rates in mail surveys. This study experimentally tests whether personalization of email invitations acts correspondingly to web survey response rates. Also, it is investigated whether personalization influences data quality. The results of the study, using a large student sample, show that personalization significantly increases the web survey response rate by 8.6 percentage points. The data quality does not appear to be affected in any major way by personalizing the email invitations. However, the analyses do show that respondents of the personalization condition tend to respond with more social desirability bias to sensitive questions. Therefore, it is concluded that personalization has positive effects on the survey response rate, but one should carefully consider whether or not to personalize when a survey on sensitive topics is conducted.     

Modelling forces of infection by using monotone local polynomials

Summary. On the basis of serological data from prevalence studies of rubella, mumps and hepatitis A, the paper describes a flexible local maximum likelihood method for the estimation of the rate at which susceptible individuals acquire infection at different ages. In contrast with parametric models that have been used before in the literature, the local polynomial likelihood method allows this age-dependent force of infection to be modelled without making any assumptions about the parametric structure. Moreover, this method allows for simultaneous nonparametric estimation of age-specific incidence and prevalence. Unconstrained models may lead to negative estimates for the force of infection at certain ages. To overcome this problem and to guarantee maximal flexibility, the local smoother can be constrained to be monotone. It turns out that different parametric and nonparametric estimates of the force of infection can exhibit considerably different qualitative features like location and the number of maxima, emphasizing the importance of a well-chosen flexible statistical model.