Bayesian analysis of multivariate survival data using Monte Carlo methods

This paper deals with the analysis of multivariate survival data from a Bayesian perspective using Markov-chain Monte Carlo methods. The Metropolis along with the Gibbs algorithm is used to calculate some of the marginal posterior distributions. A multivariate survival model is proposed, since survival times within the same group are correlated as a consequence of a frailty random block effect. The conditional proportional-hazards model of Clayton and Cuzick is used with a martingale structured prior process (Arjas and Gasbarra) for the discretized baseline hazard. Besides the calculation of the marginal posterior distributions of the parameters of interest, this paper presents some Bayesian EDA diagnostic techniques to detect model adequacy. The methodology is exemplified with kidney infection data where the times to infections within the same patients are expected to be correlated.     

Zero-inflated Poisson model with clustered regression coefficients: Application to heterogeneity learning of field goal attempts of professional basketball players

Although basketball is a dynamic process sport, played between two sides of five players each, learning some static information is essential for professional players, coaches, and team managers. In order to have a deep understanding of field goal attempts among different players, we propose a zero-inflated Poisson model with clustered regression coefficients to learn the shooting habits of different players over the court and the heterogeneity among them. Specifically, the zero-inflated model captures a large portion of the court with zero field goal attempts, and the mixture of finite mixtures model captures the heterogeneity among different players based on clustered regression coefficients and inflated probabilities. Both theoretical and empirical justification through simulation studies validate our proposed method. We apply our proposed model to data from the National Basketball Association (NBA), for learning players' shooting habits and heterogeneity among different players over the 2017–2018 regular season. This illustrates our model as a way of providing insights from different aspects.     

Social-professional status, identity, social participation and media utilization. Analysis of a complex dynamics

This article examines the link between the domain and level of occupation, on the one hand, and use of media, including internet, on the other. It adds to this investigation an analysis of identity in its relation to media use and accessibility. It challenges the hypothesis of a strong correlation between level of occupation and use and accessibility to media. It reveals complex phenomena of social homogenization and differentiation. Data is extracted from a sample of workers who completed a questionnaire which focused on use of media.     

Electricity consumption prediction with functional linear regression using spline estimators

A functional linear regression model linking observations of a functional response variable with measurements of an explanatory functional variable is considered. This model serves to analyse a real data set describing electricity consumption in Sardinia. The interest lies in predicting either oncoming weekends’ or oncoming weekdays’ consumption, provided actual weekdays’ consumption is known. A B-spline estimator of the functional parameter is used. Selected computational issues are addressed as well.     

A note on “Re-examining the law of iterated expectations for Choquet decision makers”

This note completes the main result of Zimper (Theory and decision, doi:10.1007/s11238-010-9221-8, 2010), by showing that additional conditions are needed in order the law of iterated expectations to hold true for Choquet decision makers. Due to the comonotonic additivity of Choquet expectations, the equation E[f, ν(dω)] = E[E[f(ω _{i, j} ), ν(A _{i, j} |A _i )], ν(A _i )], is valid only when the act f is comonotonic with its dynamic form, that we name “conditional certainty equivalent act”.     

Optimal simultaneous confidence bands in simple linear regression

A simultaneous confidence band provides useful information on the plausible range of an unknown regression model. For simple linear regression models, the most frequently quoted bands in the statistical literature include the hyperbolic band and the three-segment bands. One interesting question is whether one can construct confidence bands better than the hyperbolic and three-segment bands. The optimality criteria for confidence bands include the average width criterion considered by Gafarian (1964) and Naiman (1984) among others, and the minimum area confidence set (MACS) criterion of Liu and Hayter (2007). In this paper, two families of exact 1−α$1-\alpha$ confidence bands, the inner-hyperbolic bands and the outer-hyperbolic bands, which include the hyperbolic and three-segment bands as special cases, are introduced in simple linear regression. Under the MACS criterion, the best confidence band within each family is found by numerical search and compared with the hyperbolic band, the best three-segment band and with each other. The methodologies are illustrated with a numerical example and the Matlab programs used are available upon request.     

A breakpoint detection in the mean model with heterogeneous variance on fixed time intervals

Statistics and Computing - This work is motivated by an application for the homogenization of global navigation satellite system (GNSS)-derived integrated water vapour series. Indeed, these series...     

Diversity of romantic experiences in late adolescence and their contribution to identity formation

Romance constitutes a central experience in adolescence, which can take several forms including (a) serious romance with a steady partner, (b) casual and short‐lived dating, and (c) pending experiences of romantic thoughts and attempts. Using a three‐way longitudinal design, the present study examined the gender differences and developmental changes of these romantic experiences, and their cross‐lagged associations with identity processes, throughout one year in late adolescence. 389 students (63% girls) filled out questionnaires about their romantic experiences and identity processes. Girls reported more serious romance than did boys, who reported more casual dating and pending experiences. Serious romance increased over the year for both genders whereas casual dating and pending experiences continued to rise only for boys. The cross‐lagged model highlighted that serious romantic experience positively predicted identity commitments and exploration in depth whereas identity exploration in breadth positively predicted casual dating. This pattern was stable over the three time points and across gender and age groups. Overall, this study invites consideration of more diverse romantic experiences than those associated with tangible involvement. We discuss the contribution of romantic experiences to the identity dynamic.     

Management Consulting: Towards an Integrative Framework of Knowledge,Identity, and Power

This paper reviews the past 28 years of scholarship on management consulting to synthesize the field and establish more broadly its contribution to management research. Through a systematic review of 219 articles, we identify three core conceptual themes – knowledge, identity, and power – that have dominated the literature to date. Through a thematic inductive analysis of a subsection of articles, we then investigate how these themes have been defined, used, and linked. This allows us to uncover and problematize the relationships between these themes. In making explicit underlying theoretical assumptions and relationships between knowledge, identity, and power, we induce a unique framework that can guide and support future studies, instigate metaparadigmatic dialogue, and thus help consolidate the field.