Approximate Bayesian inference in semi-mechanistic models

Inference of interaction networks represented by systems of differential equations is a challenging problem in many scientific disciplines. In the present article, we follow a semi-mechanistic modelling approach based on gradient matching. We investigate the extent to which key factors, including the kinetic model, statistical formulation and numerical methods, impact upon performance at network reconstruction. We emphasize general lessons for computational statisticians when faced with the challenge of model selection, and we assess the accuracy of various alternative paradigms, including recent widely applicable information criteria and different numerical procedures for approximating Bayes factors. We conduct the comparative evaluation with a novel inferential pipeline that systematically disambiguates confounding factors via an ANOVA scheme.     

Maternal union instability and childhood mortality risk in the Global South, 2010–14

Efforts to improve child survival in lower-income countries typically focus on fundamental factors such as economic resources and infrastructure provision, even though research from post-industrial countries confirms that family instability has important health consequences. We tested the association between maternal union instability and children’s mortality risk in Africa, Latin America and the Caribbean, and Asia using children’s actual experience of mortality (discrete-time probit hazard models) as well as their experience of untreated morbidity (probit regression). Children of divorced/separated mothers experience compromised survival chances, but children of mothers who have never been in a union generally do not. Among children of partnered women, those whose mothers have experienced prior union transitions have a higher mortality risk. Targeting children of mothers who have experienced union instability—regardless of current union status—may augment ongoing efforts to reduce childhood mortality, especially in Africa and Latin America where union transitions are common.     

Heterogeneous climate effects on human migration in Indonesia

We examine the effect of anomalous temperatures, rainfall levels, and monsoon timing on migration outcomes in Indonesia. Using panel data from the Indonesian Family Life Survey and high-resolution climate data, we assess whether intra- and inter-province moves are used as a response to climatic shocks. We evaluate the relative importance of temperature, rainfall, and monsoon timing for migration. Only temperature and monsoon timing have significant effects, and these do not operate in the direction commonly assumed. Estimated effects vary according to individuals’ gender, membership in a farm household, and location. We also analyze climate effects on sources of household income, which highlights the multi-phasic nature of household responses. Results undermine narratives of a uniform global migratory response to climate change and highlight the heterogeneous use of migration as a response to such changes. By extending previous research on environmentally induced migration in Indonesia, we also highlight the sensitivity of estimates to alternative climate and migration measures.     

Effects of the social dominance orientation on environmental attitudes of Chilean university students / Efectos de la orientación a la dominancia social sobre las actitudes ambientales de universitarios chilenos

By adopting a multidimensional approach to environmental attitudes (apathy, anthropocentrism, connectedness and emotional affinity with nature), this study explores the relationships between these dimensions, social dominance orientation (SDO) and political orientation. Two hundred and sixty-two Chilean university students filled out an ad hoc online questionnaire. Two confirmatory factorial analyses showed the four typologies of environmental attitudes and the two factors for SDO, which are labelled group dominance and opposition to equality. Through hierarchical regressions, group dominance showed higher explanatory power of environmental attitudes than political orientation. Furthermore, using the bootstrap procedure we showed that group dominance mediated between political orientation and attitudes of apathy, anthropocentrism and connectedness, while opposition to equality mediated between apathy and emotional affinity. We conclude that SDO is an important variable for measuring political ideology while also providing new nuances when analysing the relationships with environmental attitudes.     

Disruptive Organisation

Organizations are driven by continuous change. Global, socio-economic and technological megatrends – demographic changes and digitalization – are the reasons for transformation. Traditional organization forms are not in line with customers‘ need. Disruptive modes of development and innovations have been intensively discussed elsewhere. The topic of disruptive organization have not been discussed towards internal and external customer relations, although of high relevance. 129 Managers answered on communication ways and the purpose of upcoming meaning for the working place/office. Two new models and five concrete recommendations have been established for upcoming future organization.     

Estimation and diagnostic analysis in skew-generalized-normal regression models

The skew-generalized-normal distribution [Arellano-Valle, RB, Gómez, HW, Quintana, FA. A new class of skew-normal distributions. Comm Statist Theory Methods 2004;33(7):1465–1480] is a class of asymmetric normal distributions, which contains the normal and skew-normal distributions as special cases. The main virtues of this distribution is that it is easy to simulate from and it also supplies a genuine expectation–maximization (EM) algorithm for maximum likelihood estimation. In this paper, we extend the EM algorithm for linear regression models assuming skew-generalized-normal random errors and we develop a diagnostics analyses via local influence and generalized leverage, following Zhu and Lee's approach. This is because Cook's well-known approach would be more complicated to use to obtain measures of local influence. Finally, results obtained for a real data set are reported, illustrating the usefulness of the proposed method.     

Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms

Competing risks occur in a time-to-event analysis in which a patient can experience one of several types of events. Traditional methods for handling competing risks data presuppose one censoring process, which is assumed to be independent. In a controlled clinical trial, censoring can occur for several reasons: some independent, others dependent. We propose an estimator of the cumulative incidence function in the presence of both independent and dependent censoring mechanisms. We rely on semi-parametric theory to derive an augmented inverse probability of censoring weighted (AIPCW) estimator. We demonstrate the efficiency gained when using the AIPCW estimator compared to a non-augmented estimator via simulations. We then apply our method to evaluate the safety and efficacy of three anti-HIV regimens in a randomized trial conducted by the AIDS Clinical Trial Group, ACTG A5095.     

Discussion of “Nonparametric Bayesian Inference in Applications”: Bayesian nonparametric methods in econometrics

The use of Bayesian nonparametrics models has increased rapidly over the last few decades driven by increasing computational power and the development of efficient Markov chain Monte Carlo algorithms. We review some applications of these models in economic applications including: volatility modelling (using both stochastic volatility models and GARCH-type models) with Dirichlet process mixture models, uses in portfolio allocation problems, long memory models with flexible forms of time-dependence, flexible extension of the dynamic Nelson-Siegel model for interest rate yields and multivariate time series models used in macroeconometrics.     

A penalized likelihood method for nonseparable space–time generalized additive models

In this paper, we study space–time generalized additive models. We apply the penalyzed likelihood method to fit generalized additive models (GAMs) for nonseparable spatio-temporal correlated data in order to improve the estimation of the response and smooth terms of GAMs. The results show that our space–time generalized additive models estimated response and smooth terms reasonable well, and in addition, the mean squared error, mean absolute deviation and coverage intervals improved considerably compared to the classic GAM. An application on particulate matter concentration in the North-Italian region of Piemonte is also presented.     

Public intellectuals,political satire and the birth of activist public relations: The case of Attic Comedy

The purpose of this article is to explore the origins of dissent public relations and to establish its emergence in the context of the ancient Greek comedy represented by Aristophanes. Indeed, Attic Comedy (also known as Old Comedy) was the first great example of today’s mass communication, in which political satire was used to dissent and protest against political and social circumstances in fifth-century BC Athens. This situation was conditioned by the Peloponnesian War and its political, economic and social consequences. From this perspective, this article also constitutes an investigation into the intellectual history of public relations, of which Aristophanes can be considered to be one of the first practitioners.