Testing Hypotheses in the Functional Linear Model

The functional linear model with scalar response is a regression model where the predictor is a random function defined on some compact set of R and the response is scalar. The response is modelled as Y =Ψ( X )+ ɛ , where Ψ is some linear continuous operator defined on the space of square integrable functions and valued in R . The random input X is independent from the noise ɛ . In this paper, we are interested in testing the null hypothesis of no effect, that is, the nullity of Ψ restricted to the Hilbert space generated by the random variable X . We introduce two test statistics based on the norm of the empirical cross-covariance operator of ( X , Y ). The first test statistic relies on a χ ² approximation and we show the asymptotic normality of the second one under appropriate conditions on the covariance operator of X . The test procedures can be applied to check a given relationship between X and Y . The method is illustrated through a simulation study.     

There goes our family friendly neighborhood: Residents’ perceptions of institutionally driven inner-city revitalization in Buffalo,NY

This article examines residents’ perceptions of inner-city revitalization in legacy cities. The analysis focuses on neighborhoods undergoing revitalization in a legacy city, Buffalo, NY. The article draws from data for a larger research project called Turning the Corner which was sponsored by the Urban Institute. The focus of that project was to identify planning strategies to address negative externalities caused by neighborhood change and heightened risks of displacement due to revitalization. Data were collected through a series of focus groups with residents and stakeholders in working-class, minority neighborhoods which were identified as being in the early stages of revitalization. Two findings emerged from the analysis. First, residents perceived urban revitalization to have a destabilizing effect on traditional neighborhoods. Second, residents perceived revitalization as detrimental to the sustainability of family-friendly neighborhoods. Insights from the analysis are used to prompt planners’ advocacy for revitalization strategies aimed at protecting minority, working-class neighborhoods when institutionally driven revitalization occurs.     

On the interaction between heterogeneity and decay in two-way flow models

In this article, we examine the role played by heterogeneity in the popular ??connections model?? of Jackson and Wolinsky (J Econ Theory 71(1):355?C365, 1996). We prove that when heterogeneity with respect to the values of resources, or the information decay parameter, depends on the identity of the player who forms the link, and the player who receives the link, all networks can be supported as Nash. Moreover, we show that Nash networks may not always exist. Interestingly, in the absence of decay, neither result occurs in a model with value heterogeneity. Finally, we show that when reducing heterogeneity, all networks cannot be supported as Nash, and the non-existence problem also disappears.     

Permuted Sample Entropy

Sample entropy (SaEn) was recently developed to quantify the amount of regularity in data. However, the computation of this feature in an online application is infeasible. In this work, we examine a heuristic approach using permuted limited number of samples to estimate SaEn and discuss estimation variability in this context. We conclude that the computation of permuted SaEn provides a fair estimate of time series regularity that can be used in online applications.     

Fast,closed-form,and efficient estimators for hierarchical models with AR(1) covariance and unequal cluster sizes

This article is concerned with statistically and computationally efficient estimation in a hierarchical data setting with unequal cluster sizes and an AR(1) covariance structure. Maximum likelihood estimation for AR(1) requires numerical iteration when cluster sizes are unequal. A near optimal non-iterative procedure is proposed. Pseudo-likelihood and split-sample methods are used, resulting in computing weights to combine cluster size specific parameter estimates. Results show that the method is statistically nearly as efficient as maximum likelihood, but shows great savings in computation time.     

The validation of surrogate end points by using data from randomized clinical trials: a case-study in advanced colorectal cancer

Summary.  In many therapeutic areas, the identification and validation of surrogate end points is of prime interest to reduce the duration and/or size of clinical trials. Buyse and co-workers and Burzykowski and co-workers have proposed a validation strategy for end points that are either normally distributed or (possibly censored) failure times. In this paper, we address the problem of validating an ordinal categorical or binary end point as a surrogate for a failure time true end point. In particular, we investigate the validity of tumour response as a surrogate for survival time in evaluating fluoropyrimidine-based experimental therapies for advanced colorectal cancer. Our analysis is performed on data from 28 randomized trials in advanced colorectal cancer, which are available through the Meta-Analysis Group in Cancer.     

Socially and privately optimal shareholder activism

This paper aims to evaluate the private and social gains of shareholder activism in an optimal contracting framework involving dispersed shareholders who may become active. The social gains are based on the welfare to stake holders in the firm, whereas the private gains are based on shareholder wealth only. Active shareholders influence the contracting game with the CEO, and therefore also the size and the distribution of the surplus to be split between the shareholders and the CEO. Although the model is very simple and focussing on the creation and distribution of welfare between the shareholders and the CEO, we nonetheless identify surprising divergence between the private and social profitability of shareholder activism. Shareholder activism that is privately profitable is not necessarily socially profitable. The distributional effects of shareholder activism may dominate the efficiency effects to make shareholder activism a negative social NPV project.      

Development of the Sexual Five-Facet Mindfulness Questionnaire (FFMQ-S): Validation Among a Community Sample of French-Speaking Women

It has been recently demonstrated that mindfulness-based intervention may be particularly suitable for addressing sexual difficulties in women. Although the Five-Facet Mindfulness Questionnaire (FFMQ) is currently one of the most widely used scales to assess mindfulness, no adaptation and validation of the FFMQ to measure female sexual functioning has been published. The main aim of this study was to develop and validate a sexual version of the Five Facets Mindfulness Questionnaire (FFMQ-S) to specifically measure mindfulness in the context of sexual encounters. A total of 251 healthy, French-speaking female volunteers were administered the FFMQ-S, the original FFMQ, and the Female Sexual Distress Scale (FSDS-R). Confirmatory factor analyses indicated that the FFMQ-S exhibits a five-factor model, as implied by the original FFMQ. Good scale reliability was observed. The FFMQ-S showed significant correlations with the FSDS-R and the usual FFMQ. Scores on the FFMQ-S correlated significantly more negatively with the total FSDS-R score than with the total score of the original version of the FFMQ. These findings clearly support the relevance of developing a version of the FFMQ tailored to sexual functioning.     

On the Weibull-Gamma frailty model, its infinite moments, and its connection to generalized log-logistic, logistic, Cauchy, and extreme-value distributions

It is shown that the commonly used Weibull-Gamma frailty model has a finite number of finite moments only and that its marginal distribution generalizes the log-logistic distribution. In some cases there is not even a finite variance, and there are cases without a single finite moment. Upon transformation to the entire real line, generalized logistic and generalized Cauchy distributions are introduced and their connection with the previous ones established, as well as with the extreme-value distribution. Apart from intrinsic and classroom value, the family can be of use when formulating non-informative priors in Bayesian data analysis. Also, gauging the amount of finite moments is important when checking regularity conditions in the Weibull-Gamma model. Our findings are illustrated using data from survival in cancer patients.