Statistical consulting interactions: a personal view

There are several components to every consulting project. The most important ones are the scientific/industrial partners, the background and goals of the project, and data. A statistician has to interact successfully with every component for the project to be a success and an essential step is to encourage the project partners to interact with their own data. There is no better way to ensure that domain knowledge is fully integrated into any analysis. Partners are not always explicit about what they know, about what is possible and about what they want. It is not always clear to them either. Consulting in projects is more of a process than the accomplishment of a task, so continual interaction is needed. Sometimes this is easy, sometimes it is more difficult. This does not always have much to do with the intrinsic difficulty of the subject matter.     

Propriétés dans L2 et estimation des processus purement bilinéaires et strictement superdiagonaux à coefficients périodiques

L₂‐properties and estimation of purely bilinear and strictly superdiagonal time series models with periodic coefficients The authors consider the subclass of purely bilinear and strictly superdiagonal time series models with periodic coefficients. Indeed, thanks to their possible application to a wide variety of fields including economics and finance, bilinear time series models with time‐dependent coefficients have recently been the object of attention in the statistical literature. The authors give conditions ensuring the existence of a causal solution in L², the invertibility and the existence of higher‐order moments. The problem of estimating the parameters is also investigated through an approach based on second and third empirical moments. The authors numerically illustrate their theoretical results via Monte Carlo simulations.     

Emotional Experience as a Function of Social Context: The Role of the Other

Inconsistencies in previous findings concerning the relationship between emotion and social context are likely to reflect the multi-dimensionality of the sociality construct. In the present study we focused on the role of the other person by manipulating two aspects of this role: co-experience of the event and expression of emotion. We predicted that another's co-experience and expression would affect emotional responses and that the direction of these effects would depend upon the manipulated emotion and how the role of the other person is appraised. Participants read vignettes eliciting four different emotions: happiness, sadness, anxiety, and anger. As well as an alone condition, there were four conditions in which a friend was present, either co-experiencing the event or merely observing it, and either expressing emotions consistent with the event or not showing any emotion. There were significant effects of co-experience in the case of anger situations, and of expression in the case of happiness and sadness situations. Social appraisal also appeared to influence emotional response. We discuss different processes that might be responsible for these results.     

A Generalization to Bivariate Mittag–Leffler and Bivariate Discrete Mittag–Leffler Autoregressive Processes

A generalization of the Gaver and Lewis (1980 Gaver , D. P. , Lewis , P. A. W. ( 1980 ). First order autoregressive gamma sequences and point processes . Adv. Appl. Probab. 12 : 727 – 745 .[Crossref], [Web of Science ®] , [Google Scholar]) model of first-order autoregressive process with marginals as bivariate Mittag–Leffler distribution is obtained. A necessary and sufficient condition for stationarity of the process is established. Autoregressive process with marginals follow bivariate discrete Mittag–Leffler distribution is also developed. The unknown parameters of the processes are estimated and some numerical results of the estimations are given.     

Social Psychological Factors in Lifestyle Change and Their Relevance to Policy

Crises in obesity and changes in the environment illustrate the need to change problematic behaviors and lifestyles in large segments of the population. This article uses social psychological theory and research to understand methods for facilitating lifestyle change. A basic assumption in the social psychological perspective is that the environment and the person interact to determine behavior. Both factors are important for understanding "upstream" and "downstream" approaches to lifestyle change ( McKinlay, 1993 ; Verplanken & Wood, 2006 ) and consideration of one factor without the other may be disastrous. We review evidence from within and outside of the health context to illustrate the upstream and downstream approaches and then describe implications for public policy and intervention. The evidence and recommendations encompass a wide range of behaviors, ranging from speeding and intoxicated driving to eating an unhealthy diet and energy conservation. When armed with the relevant social psychological theory and evidence, lifestyle change campaigns are likely to be successful.     

Degree and Direction of Paid Employee/Volunteer Interchange in Nonprofit Organizations

This study builds on an earlier one (Handy, Mook, and Quarter 2008) that examined the degree of interchangeability between volunteers and paid employees in nonprofit organizations. In the current study, we surveyed 836 nonprofits in Canada to understand what factors determine the degree of interchange between paid employees and volunteers, bearing in mind that this interchange can go in two directions: paid employees for volunteers and volunteers for paid employees. We found the degree of interchange to be widespread and in both directions. One of the most important predictors of the likelihood of interchange was the number of full‐time employees, suggesting that interchangeability occurs less frequently in organizations with a larger number of employees than in those with fewer employees. Religious congregations and organizations with workload increases were more likely to interchange tasks among volunteers and paid staff.     

Collaboration outcomes in a public sector: impact of governance,leadership, interdependence and relational capital

Collaboration between public agencies is critical to address social issues effectively. The main objective of this research was to identify the factors that lead to successful achievement of desired collaboration outcomes that could eventually lead to societal outcomes. The factors identified were: transformational leadership, governance, interdependence, and relational capital. An integrated framework was developed based on collaboration governance framework (CGF) of Ansell and Gash (J Public Adm Res Theory 18:543–571, 2008). The CGF framework has integrated the following four broad variables that are responsible for achieving the desired collaboration outcomes: starting conditions, institutional design, leadership, and collaborative process. The study was conducted in Malaysia by sending questionnaires to 500 officers in various ministries who were involved in planning, formulating, and implementing public policies. The main findings of this study are: (1) transformational leadership influences governance, interdependence, relational capital, and collaboration outcomes; (2) governance has impact on relational capital, interdependence, and collaboration outcomes; (3) relational capital and interdependence result in positive collaboration outcomes; (4) dimensions of governance are inter-related; and (5) interdependence and relational capital are strongly correlated. This research adds significantly to the literature on collaborative governance. The implications and limitations of the study are discussed.