Cohort patterns in adult literacy skills: How are new generations doing?

Skills are core elements of the socio-economic prospects of individuals, while they also improve national productivity, growth and social cohesion. Understanding how skills evolve over time and what drives their evolution has become a policy priority of many European countries. Using the 1994–1998 International Adult Literacy Survey (IALS) and the 2012 Survey on Adult Skills (PIAAC) we build synthetic cohorts and examine how the population gains, loses or preserves cognitive skills (literacy) over time. While, as expected, deterioration in the level of skills due to ageing is common to almost all the European countries studied, for some of them concerns arise for the occurrence of skill deterioration across generations, especially among less well-educated and medium-educated individuals. Certain countries appear to be doing a poorer job in providing the necessary literacy skills over successive generations.     

Joint projections of temperature and precipitation change from multiple climate models: a hierarchical Bayesian approach

Summary.  Posterior distributions for the joint projections of future temperature and precipitation trends and changes are derived by applying a Bayesian hierachical model to a rich data set of simulated climate from general circulation models. The simulations that are analysed here constitute the future projections on which the Intergovernmental Panel on Climate Change based its recent summary report on the future of our planet's climate, albeit without any sophisticated statistical handling of the data. Here we quantify the uncertainty that is represented by the variable results of the various models and their limited ability to represent the observed climate both at global and at regional scales. We do so in a Bayesian framework, by estimating posterior distributions of the climate change signals in terms of trends or differences between future and current periods, and we fully characterize the uncertain nature of a suite of other parameters, like biases, correlation terms and model-specific precisions. Besides presenting our results in terms of posterior distributions of the climate signals, we offer as an alternative representation of the uncertainties in climate change projections the use of the posterior predictive distribution of a new model's projections. The results from our analysis can find straightforward applications in impact studies, which necessitate not only best guesses but also a full representation of the uncertainty in climate change projections. For water resource and crop models, for example, it is vital to use joint projections of temperature and precipitation to represent the characteristics of future climate best, and our statistical analysis delivers just that.     

Social Participation, Sense of Community and Social Well Being: A Study on American, Italian and Iranian University Students

Aim of the study was to assess the relationship between social participation and Sense of Community in a sample of University students and the impact of such variables on Social well being. A further aim was to assess the generality of the relationships between these constructs across different countries, and specifically, the USA, Italy and Iran. The sample includes 200 Italian, 125 American and 214 Iranian University students, male and female. Results show higher levels of social participation, Sense of Community and Social well being among American students. Sense of Community is positively correlated with social participation in all three samples; however, only among Italian students social participation positively predicts Social well being. Implications of results will be discussed.     

Polymorphism-screening: genetic testing for predisposition—guidance for technology assessment

Health policy is increasingly confronted with the demand for financing genetic testing on inherited susceptibility to disease. Tests on polymorphism/SNP associated with multicausal and chronic conditions are already offered in private commercial institutions or in academic hospitals. The increasing pressure on public health services to offer SNP testing leads to first methodological approaches for a generally valid regulatory framework applicable for inclusion or refusal of genetic tests into the public health services. Systematic search in Medline, Embase and the Web for methodological papers or guidelines for the assessment of polymorphism-screening. Since genetic testing has not only clinical and economic effects on health care, but also primarily ethical consequences by profiling our understanding of “health” and “disease”, this paper gives an overview of relevant aspects and background information to consider in the assessment of genetic tests. Although 2–3 million SNPs are identified and the journals are full of reported “significant” associations between disease and mutation, only a few can be replicated unequivocally. The ACCE (Analytic and Clinical Validity, Clinical utility; Ethical, legal and social implications)-framework was developed by the Center of Disease Control for the assessment of genetic testing. This standardised appraisal approach proposes collecting and evaluating: (a) Prevalence, genotype-/phenotype-relation. (b) Clinical presentation: natural history; the different expressions of disease. (c) Performance of the genetic test. (d) Implications for therapy and prevention. (e) Conclusion for clinical applications of risk-profiling of health on their susceptibility to disease and/or for clarification of disease for therapy planning. Since genetic testing is urging its way into the health care system, the actual danger is, that population screening starts before valid evidence from big prospective studies have been carried out and delivered proofs of direct causal associations. Before diffusing into the health care system we are suggesting to take a cautious and standardised approach.     

“Reactive Ethnicity” or “Assimilation”? Statements,Arguments, and First Empirical Evidence for Labor Migrants in Germany

In this article, we scrutinize the often stated assumption that labor migrants in Germany turn away from integration and reaffirm their ethnicity by examining their identificational, cognitive, and social assimilation processes. Using data from the German Socio‐economic Panel, we present trend analyses of different hostland‐ and homeland‐related indicators for the past fifteen years. Results are presented separately for first‐ and second‐generation migrants from Turkey, the EU, and the former Yugoslavia. While not all assimilation‐related indicators change a great deal over time, they show at least a substantial difference between the first and the second generation. With regard to the homeland‐related indicators, the results by no means suggest that Turkish migrants try to compensate for their comparatively disadvantaged social status by revitalizing ethnic cultural habits or homeland‐oriented identifications.     

Identifiability and estimation of recursive max‐linear models

We address the identifiability and estimation of recursive max‐linear structural equation models represented by an edge‐weighted directed acyclic graph (DAG). Such models are generally unidentifiable and we identify the whole class of DAG s and edge weights corresponding to a given observational distribution. For estimation, standard likelihood theory cannot be applied because the corresponding families of distributions are not dominated. Given the underlying DAG, we present an estimator for the class of edge weights and show that it can be considered a generalized maximum likelihood estimator. In addition, we develop a simple method for identifying the structure of the DAG. With probability tending to one at an exponential rate with the number of observations, this method correctly identifies the class of DAGs and, similarly, exactly identifies the possible edge weights.     

Bayesian model selection for D‐vine pair‐copula constructions

In recent years analyses of dependence structures using copulas have become more popular than the standard correlation analysis. Starting from Aas et al. ( 2009 ) regular vine pair‐copula constructions (PCCs) are considered the most flexible class of multivariate copulas. PCCs are involved objects but (conditional) independence present in data can simplify and reduce them significantly. In this paper the authors detect (conditional) independence in a particular vine PCC model based on bivariate t copulas by deriving and implementing a reversible jump Markov chain Monte Carlo algorithm. However, the methodology is general and can be extended to any regular vine PCC and to all known bivariate copula families. The proposed approach considers model selection and estimation problems for PCCs simultaneously. The effectiveness of the developed algorithm is shown in simulations and its usefulness is illustrated in two real data applications. The Canadian Journal of Statistics 39: 239–258; 2011 © 2011 Statistical Society of Canada