Designing two factor experiments for selecting interactions

This paper considers the problem of devising a single stage procedure for selecting the treatment combination associated with the largest interaction in a two-factor rfx× c experiment having independent normally distributed observations with common known variance. The intuitive procedure based on the best linear unbiased estimators of the population interactions is employed. Initially an indifference zone formulation is used; the problem of determining the least favorable configuration is reduced to a nonlinear programming problem with log concave objective function and a convex polytope as feasible region. A solution technique is introduced in the context of an illustrative example. The problem is also considered using a preferred population formulation; this approach requires a strengthened version of the indifference zone probability requirement. It is shown that the same sample size guarantees this requirement as does the earlier one.     

Detection of interactions in experiments on large numbers of factors

One of the main advantages of factorial experiments is the information that they can offer on interactions. When there are many factors to be studied, some or all of this information is often sacrificed to keep the size of an experiment economically feasible. Two strategies for group screening are presented for a large number of factors, over two stages of experimentation, with particular emphasis on the detection of interactions. One approach estimates only main effects at the first stage (classical group screening), whereas the other new method (interaction group screening) estimates both main effects and key two-factor interactions at the first stage. Three criteria are used to guide the choice of screening technique, and also the size of the groups of factors for study in the first-stage experiment. The criteria seek to minimize the expected total number of observations in the experiment, the probability that the size of the experiment exceeds a prespecified target and the proportion of active individual factorial effects which are not detected. To implement these criteria, results are derived on the relationship between the grouped and individual factorial effects, and the probability distributions of the numbers of grouped factors whose main effects or interactions are declared active at the first stage. Examples are used to illustrate the methodology, and some issues and open questions for the practical implementation of the results are discussed.     

美国中东政策调整与中、美、阿关系互动

迫于国际形势和国内外舆论压力，布什政府从2007年开始调整中东政策，把遏制伊朗作为政策重点。为此，美国重新扮演了巴以和平调解人的角色，主动缓和与阿拉伯国家关系。美阿关系的发展对正在积极参与中东事务的中国具有重要意义。未来中东仍是美国对外战略关注的重点，“美国因素”在中阿关系中会更加频繁，三者互动将更为密切。中国对中东问题的积极立场及对中东事务的主动参与，对于推动中、美、阿关系的良性互动将产生深远影响。     

论学报发展与学科建设的互动关系

文章论述了学报发展与学科建设之间的互动关系,认为两者如能形成良好的互动关系,必能相互促进,共同提高,并对如何实现这种互动进行了探索.     

孵化互动、专用性人力资本和在孵企业成功毕业

基于合作生产理论,本文以307个新创在孵企业为样本,构建生存模型研究孵化互动介入模式和创业专用性人力资本对在孵企业成功毕业的影响。研究发现,行业专用性人力资本、创业家庭背景促成了创业成功,而创业经历对创业成功没有显著影响。同时,孵化互动在促成在孵企业成功毕业方面的调节作用则表现出很大的异质性:孵化互动模式Ⅳ和Ⅴ对行业专用性人力资本有促进性调节作用,而所有孵化互动模式对家庭背景的存在都有抑制性调节作用,但是孵化互动模式对创业经历没有显著的影响。这说明,对于包含诸多隐性成分的行业专用性知识,孵化器经理的参与意愿和介入频率是影响孵化效果的关键因素;同时,孵化互动部分替代了家庭支持的作用,降低了创业者对家庭的依赖。     

Accounting for clinical covariates and interactions in ranking genomic markers using ROC

In biomedical research, profiling is now commonly conducted, generating high-dimensional genomic measurements (without loss of generality, say genes). An important analysis objective is to rank genes according to their marginal associations with a disease outcome/phenotype. Clinical-covariates, including for example clinical risk factors and environmental exposures, usually exist and need to be properly accounted for. In this study, we propose conducting marginal ranking of genes using a receiver operating characteristic (ROC) based method. This method can accommodate categorical, censored survival, and continuous outcome variables in a very similar manner. Unlike logistic-model-based methods, it does not make very specific assumptions on model, making it robust. In ranking genes, we account for both the main effects of clinical-covariates and their interactions with genes, and develop multiple diagnostic accuracy improvement measurements. Using simulation studies, we show that the proposed method is effective in that genes associated with or gene–covariate interactions associated with the outcome receive high rankings. In data analysis, we observe some differences between the rankings using the proposed method and the logistic-model-based method.     

Optimal paired comparison designs for first-order interactions

In many fields of applications paired comparisons are used in which either full or partial profiles of the alternatives are presented. For this situation we introduce an appropriate model and derive optimal designs in the presence of interactions when all attributes have the same number of levels.     

Does death really make us equal? Educational attainment and resource compensation after paternal death in Finland

Attempts to explain the persistent importance of family background for children's educational attainment typically highlight the ways in which parents pass down educational, economic and social resources to their children. However, parental resources may also play a crucial role for preventing family crises from spiraling into cumulative disadvantage. To study such compensation processes, we examine the consequences of a father's death on children's educational trajectories, using a Finnish register-based sample of children born between 1982 and 1987. The results based on multilevel linear probability models both support and contradict our compensation hypothesis. Children who lost their father were not more likely to drop out of upper secondary school, as long as their surviving mother had high levels of socioeconomic resources. Similar compensation processes were visible in the case of entering polytechnic higher education. However, with regard to university attendance, bereavement noticeably reduced the traditional advantage of children with high-resource parents.     

Interactions in new product development: How the nature of the NPD process influences interaction between teams and management

Effective interaction across organisational boundaries is a critical success factor in new product development (NPD). However, few studies have investigated how different mechanisms enable effective interaction across organisational and particularly hierarchical boundaries.This study explores how the formality of the NPD process influences the nature of interactions across different organisational boundaries and specifically identifies interaction mechanisms used across hierarchical boundaries. Cross-sectional interviews were conducted in nine firms. Findings highlight that in firms with a formalised NPD process, interactions tend to have a transactional/managerial bias. In contrast, in firms where the NPD process is flexible, interactions have a more social objective.