Rate estimation in partially observed Markov jump processes with measurement errors

We present a simulation methodology for Bayesian estimation of rate parameters in Markov jump processes arising for example in stochastic kinetic models. To handle the problem of missing components and measurement errors in observed data, we embed the Markov jump process into the framework of a general state space model. We do not use diffusion approximations. Markov chain Monte Carlo and particle filter type algorithms are introduced which allow sampling from the posterior distribution of the rate parameters and the Markov jump process also in data-poor scenarios. The algorithms are illustrated by applying them to rate estimation in a model for prokaryotic auto-regulation and the stochastic Oregonator, respectively.     

Promoting Development in Weak Institutional Environments: The Understanding and Transmission of Sustainability by NGOS in Latin America

Non-governmental organizations (NGOs) are a major institutional force in promoting sustainable development, especially in institutional environments where governments have often not been able to assume the role of development agent. Despite this importance, the approach of Latin American NGOs to sustainability has received only little attention so far and respective research is scarce. To address this research gap, we conducted an online survey of 306 Latin American NGOs, investigating their understanding of sustainability and how they seek to transmit it. Due to the lack of previous empirical studies, our study is exploratory in nature and examines eight research categories: (1) NGOs definition of sustainability; (2) the role they see for themselves in its promotion, (3) dimensions of sustainability judged as important, (4) stakeholders and (5) partners considered, (6) motives for pursuing sustainability, (7) forms of implementation, and (8) measures regarded as necessary for spreading it further. Our findings are discussed against the institutional environment of Latin America, as we assume that the understanding and transmission of sustainability is contextual in nature. Our study shows that the sustainability concept of the sample NGOs is broad and that they take a wide variety of efforts for implementing it. Exploratory and confirmatory factor analyses confirmed the reliability and validity of the eight-component-model we applied for our study. Thus, it serves as a valuable starting point for future research into the “terra incognita” of Latin American NGOs’ approach to sustainability.     

Plastic surgery in gynaecology: Factors affecting women’s decision to undergo labiaplasty. Mind the risk of body dysmorphic disorder: A review

ABSTRACT

Aesthetic surgery of the female genitalia is on the rise. Many procedures are performed. Body dysmorphic disorder (BDD) is a psychiatric disorder and often goes unrecognized in plastic surgery. This review examines actual knowledge of plastic surgery in gynecology, knowledge of motivational factors of women, and BDD. We carried out a systematic electronic search. We used a combination of relevant keywords to construct the search strategy. Included studies were systematic reviews or primary studies published 1990–2017 and containing information about BDD. Reviewers independently assessed study eligibility, extracted data, and assessed quality, undertaking narrative synthesis. The research revealed a variety of plastic procedures available and why women consider undergoing labia reduction surgery.     

A convergent algorithm for a generalized multivariate isotonic regression problem

Sasabuchi et al. (Biometrika 70(2):465–472, 1983) introduces a multivariate version of the well-known univariate isotonic regression which plays a key role in the field of statistical inference under order restrictions. His proposed algorithm for computing the multivariate isotonic regression, however, is guaranteed to converge only under special conditions (Sasabuchi et al., J Stat Comput Simul 73(9):619–641, 2003). In this paper, a more general framework for multivariate isotonic regression is given and an algorithm based on Dykstra’s method is used to compute the multivariate isotonic regression. Two numerical examples are given to illustrate the algorithm and to compare the result with the one published by Fernando and Kulatunga (Comput Stat Data Anal 52:702–712, 2007).     

Slum Residence and Child Health in Developing Countries

Continued population growth and increasing urbanization have led to the formation of large informal urban settlements in many developing countries in recent decades. The high prevalence of poverty, overcrowding, and poor sanitation observed in these settlements—commonly referred to as “slums”—suggests that slum residence constitutes a major health risk for children. In this article, we use data from 191 Demographic and Health Surveys (DHS) across 73 developing countries to investigate this concern empirically. Our results indicate that children in slums have better health outcomes than children living in rural areas yet fare worse than children in better-off neighborhoods of the same urban settlements. A large fraction of the observed health differences appears to be explained by pronounced differences in maternal education, household wealth, and access to health services across residential areas. After we control for these characteristics, children growing up in the slums and better-off neighborhoods of towns show levels of morbidity and mortality that are not statistically different from those of children living in rural areas. Compared with rural children, children living in cities (irrespective of slum or formal residence) fare better with respect to mortality and stunting but not with respect to recent illness episodes.     

Influence measures based on confidence ellipsoids in general linear regression model with correlated regressors

In this paper, we investigated the Andrews–Pregibon (AP), COVRATIO and Cook–Weisberg (CW) statistics to determine the influential observations on the confidence ellipsoids in linear regression model with correlated errors and correlated regressors. A real example and a Monte Carlo simulation study are given to detect the effects of autocorrelation coefficient and ridge parameter on the AP, COVRATIO and CW statistics.     

The Mass Emigration Context of Lithuania: Patterns and Policy Options

Lithuania represents one of the rare cases in which a state with relatively high standards for maintaining population statistics is experiencing mass emigration. In light of the policy initiatives undertaken by the Lithuanian government to address the issue of emigration, this study aims to improve our understanding of how, in this mass emigration context, emigration events are connected to specific socio‐economic characteristics of individuals and variation in local socio‐economic conditions. We analyse census and vital registration data covering the whole working‐age population of Lithuania during the period 2011‐2012. Our findings indicate that when assessing the likelihood of emigration events, individual‐level characteristics such as employment status, educational attainment, and prior migration experience are highly relevant. However, the importance of these characteristics differs by gender. We also detect considerable spatial variation in emigration rates across Lithuanian municipalities. Our outcomes provide new insights for the development of cohesive migration policies in Lithuania.