Cytometry inference through adaptive atomic deconvolution

In this paper, we consider a statistical estimation problem known as atomic deconvolution. Introduced in reliability, this model has a direct application when considering biological data produced by flow cytometers. From a statistical point of view, we aim at inferring the percentage of cells expressing the selected molecule and the probability distribution function associated with its fluorescence emission. We propose here an adaptive estimation procedure based on a previous deconvolution procedure introduced by Es, Gugushvili, and Spreij [(2008), ‘Deconvolution for an atomic distribution’, Electronic Journal of Statistics, 2, 265–297] and Gugushvili, Es, and Spreij [(2011), ‘Deconvolution for an atomic distribution: rates of convergence’, Journal of Nonparametric Statistics, 23, 1003–1029]. For both estimating the mixing parameter and the mixing density automatically, we use the Lepskii method based on the optimal choice of a bandwidth using a bias-variance decomposition. We then derive some convergence rates that are shown to be minimax optimal (up to some log terms) in Sobolev classes. Finally, we apply our algorithm on the simulated and real biological data.     

Properties of the weighted log‐rank test in the design of confirmatory studies with delayed effects

Proportional hazards are a common assumption when designing confirmatory clinical trials in oncology. This assumption not only affects the analysis part but also the sample size calculation. The presence of delayed effects causes a change in the hazard ratio while the trial is ongoing since at the beginning we do not observe any difference between treatment arms, and after some unknown time point, the differences between treatment arms will start to appear. Hence, the proportional hazards assumption no longer holds, and both sample size calculation and analysis methods to be used should be reconsidered. The weighted log‐rank test allows a weighting for early, middle, and late differences through the Fleming and Harrington class of weights and is proven to be more efficient when the proportional hazards assumption does not hold. The Fleming and Harrington class of weights, along with the estimated delay, can be incorporated into the sample size calculation in order to maintain the desired power once the treatment arm differences start to appear. In this article, we explore the impact of delayed effects in group sequential and adaptive group sequential designs and make an empirical evaluation in terms of power and type‐I error rate of the of the weighted log‐rank test in a simulated scenario with fixed values of the Fleming and Harrington class of weights. We also give some practical recommendations regarding which methodology should be used in the presence of delayed effects depending on certain characteristics of the trial.     

论适应性表征及其方法论意义

适应性是主体适应其环境的特性,是物理演化系统和生物演化系统的本质属性,反映在认知上就是适应性表征。适应性表征也因此成为知识显现的方式和创造的核心,具有协调性、匹配性、互补性、模拟性和类比性,其表现方式有直接具象表征、间接具象表征、直接抽象表征和间接抽象表征,分别对应于经验主义、建构经验主义、理性主义和科学实在论。适应性表征的实现是通过科学理论核心概念的变化、定律的凝练、理论的更替、模型推理和世界观的改变展开的,具有经验上的适当性。这种经验适当性不仅是感知层次的体验,更是一种认知模式。在认知意义上,经验也是基于心理模型的,心理建模的路径有思想语言、心理表象、心理命题、思想实验和心理模拟推理。这种基于心理建模的适应性表征为科学认知和科学发现提供了有益的方法论。     

基于大数据合作资产的适应性创新--数字经济的创新逻辑(二)

万物互联时代,数据被认为是与土地、劳动、资本、知识、技术和管理并重的第七大生产要素。当前,多样化的商业实践创新对数据价值的深度挖掘正在突破经济学在传统意义上对数据及其价值的限定,然而,理论上对此还缺乏相应的概念凝练和探讨。本文从企业与消费者价值共创角度提出大数据合作资产的概念,并探讨基于大数据合作资产和适应性创新的数字经济创新逻辑。研究表明:大数据合作资产是一种互动性资源,是企业与消费者在数字化服务交互中成为能够被另一方所拥有和利用并能创造当前或未来经济收益的数字化资产;单纯拥有异质资源不一定会形成合作资产,只有当异质化资源被有效整合、且被使用于企业与消费者服务交换中,才能体现为行动者创造收益的价值潜力;协同演化促进了企业与消费者对彼此的适应性调整,基于大数据合作资产激发以即时调整、即时反馈和难以预测为特征的适应性创新,进而促进了数字经济创新。     

考虑自适应行为的研发网络风险传播模型构建及仿真

构建风险视域下研发网络企业自适应行为规则，基于SIS模型构建研发网络风险传播模型，运用数值仿真的方法通过改变模型参数探索在考虑自适应行为的情况下研发网络的风险传播规律，研究结果表明：（1）C1策略增强了网络的层次性和社团强度，一定程度上抑制了研发网络中风险的传播；C2策略下节点之间新连接的建立更多是基于临近性的考量，容易陷入路径依赖和能力陷阱；（2）研发网络企业的自适应行为会导致社团强度的涨落，平均路径长度的下降以及平均聚类系数的增长充分体现出C1策略的有效性。（3）C1策略下，断边概率p与I*之间呈现"U"型相关关系；在C2策略下随着断边概率p的增长I*逐渐降低。（4）在C1策略和C2策略下，随着参数ζ的增长I*也随之增长，可知组织依赖水平是研发网络风险传播控制中需要重点关注的因素。本文揭示了在考虑自适应行为的情况下研发网络的风险传播规律，为网络化运作背景下研发网络治理提供理论依据。     

Toward Father‐friendly Parenting Interventions: A Qualitative Study

Levels of father participation in parenting interventions are often very low, yet little is known about the factors which influence father engagement. We aimed to qualitatively explore perceived barriers to, and preferences for, parenting interventions in a community sample of fathers. Forty‐one fathers across nine focus groups were interviewed using a semi‐structured interview. Data were analysed using inductive thematic analysis. Key barriers to father participation identified included: the perception that interventions are mother‐focused; beliefs about gender roles regarding parenting and help‐seeking; mothers’ role as ‘gatekeeper’; lack of knowledge and awareness of parenting interventions; and lack of relevance of interventions. Fathers reported preferences for specific content and intervention features, facilitator characteristics, practical factors, and highlighted the need for father‐targeted recruitment and advertising. Many of the barriers and preferences identified are consistent with previous research; however, fathers’ beliefs and attitudes around gender roles and help‐seeking, as well as the perception that interventions are predominantly mother‐focused, may be key barriers for community fathers. Strategies to overcome these barriers and better meet the needs of fathers in promoting and delivering parenting interventions are discussed.     

Modifications of sequential designs in bioequivalence trials

Bioequivalence (BE) studies are designed to show that two formulations of one drug are equivalent and they play an important role in drug development. When in a design stage, it is possible that there is a high degree of uncertainty on variability of the formulations and the actual performance of the test versus reference formulation. Therefore, an interim look may be desirable to stop the study if there is no chance of claiming BE at the end (futility), or claim BE if evidence is sufficient (efficacy), or adjust the sample size. Sequential design approaches specially for BE studies have been proposed previously in publications. We applied modification to the existing methods focusing on simplified multiplicity adjustment and futility stopping. We name our method modified sequential design for BE studies (MSDBE). Simulation results demonstrate comparable performance between MSDBE and the original published methods while MSDBE offers more transparency and better applicability. The R package MSDBE is available at https://sites.google.com/site/modsdbe/ . Copyright © 2015 John Wiley & Sons, Ltd.     

Heteroscedasticity and Distributional Assumptions in the Censored Regression Model

Data censoring causes ordinary least-square estimators of linear models to be biased and inconsistent. The Tobit estimator yields consistent estimators in the presence of data censoring if the errors are normally distributed. However, nonnormality or heteroscedasticity results in the Tobit estimators being inconsistent. Various estimators have been proposed for circumventing the normality assumption. Some of these estimators include censored least absolute deviations (CLAD), symmetrically censored least-square (SCLS), and partially adaptive estimators. CLAD and SCLS will be consistent in the presence of heteroscedasticity; however, SCLS performs poorly in the presence of asymmetric errors. This article extends the partially adaptive estimation approach to accommodate possible heteroscedasticity as well as nonnormality. A simulation study is used to investigate the estimators’ relative performance in these settings. The partially adaptive censored regression estimators have little efficiency loss for censored normal errors and appear to outperform the Tobit and semiparametric estimators for nonnormal error distributions and be less sensitive to the presence of heteroscedasticity. An empirical example is considered, which supports these results.     

Vaginal births after caesarean: What does Google think about it?

AimVaginal birth after caesarean (VBAC) is a relatively safe alternative to repeat caesarean birth in the proper context. This important decision to undergo an elective caesarean versus VBAC is ultimately a decision of the mother. The purpose of our study was to assess the quality of online information in relation to VBAC collected using the most common search engine: Google.MethodsThe 10 most common hit sites for the keywords “VBAC” and “Vaginal birth after caesarean” were evaluated using the search engine Google. The quality of websites was rated based on the Silberg scale for accountability, the modified Abbott's criteria for presentation and the SMOG index for readability. The content of each website was compared to the Society of Obstetricians and Gynecologists of Canada (SOGC) guidelines for VBAC.Findings13 out of 20 identified websites met the adequate criteria for accountability, with 85% of the websites indicating authorship. 11 websites were deemed aesthetically agreeable. The target audience, assessed by the readability score, was notably above the non-medical population with an average SMOG index score of 14.75. Only half of the websites contained recommendations, as detailed by the SOGC guidelines.ConclusionAlmost all sites target a higher academic level, making it beyond the comprehension of the general population. Woman friendly web-assessment tools should be provided to enable pregnant women to take an active role in their decision making.     

新一代信息技术驱动的产品适应性创新机制

现有产品创新研究多从用户、产品以及技术单一视角出发,然而,进入数字经济时代,在新一代信息技术驱动下,产品以用户、企业、环境多维互动的方式进行创新,呈现出特有的适应性创新特征。本文采取多案例研究方法,探讨在新一代信息技术驱动下产品适应性创新的特征和实现机制。研究发现:产品适应创新具有高频互动、即时反馈、快速适应性和用户主导创新四个显著特征,形成用户、企业、产品多方互动的适应性创新实现机制。与此同时,通过案例论证以产品、场景、用户为核心特征的产品适应创新实现机制的存在性,指出其本质是深入挖掘用户需求并实现用户需求的快速匹配。