Bayesian modeling of temporal properties of infectious disease in a college student population

A Bayesian statistical model is developed for analysis of the time-evolving properties of infectious disease, with a particular focus on viruses. The model employs a latent semi-Markovian state process, and the state-transition statistics are driven by three terms: (i) a general time-evolving trend of the overall population, (ii) a semi-periodic term that accounts for effects caused by the days of the week, and (iii) a regression term that relates the probability of infection to covariates (here, specifically, to the Google Flu Trends data). Computations are performed using Markov Chain Monte Carlo sampling. Results are presented using a novel data set: daily self-reported symptom scores from hundreds of Duke University undergraduate students, collected over three academic years. The illnesses associated with these students are (imperfectly) labeled using real-time (RT) polymerase chain reaction (PCR) testing for several viruses, and gene-expression data were also analyzed. The statistical analysis is performed on the daily, self-reported symptom scores, and the RT PCR and gene-expression data are employed for analysis and interpretation of the model results.     

New HEAVY Models for Fat-Tailed Realized Covariances and Returns

ABSTRACT

We develop a new score-driven model for the joint dynamics of fat-tailed realized covariance matrix observations and daily returns. The score dynamics for the unobserved true covariance matrix are robust to outliers and incidental large observations in both types of data by assuming a matrix-F distribution for the realized covariance measures and a multivariate Student's t distribution for the daily returns. The filter for the unknown covariance matrix has a computationally efficient matrix formulation, which proves beneficial for estimation and simulation purposes. We formulate parameter restrictions for stationarity and positive definiteness. Our simulation study shows that the new model is able to deal with high-dimensional settings (50 or more) and captures unobserved volatility dynamics even if the model is misspecified. We provide an empirical application to daily equity returns and realized covariance matrices up to 30 dimensions. The model statistically and economically outperforms competing multivariate volatility models out-of-sample. Supplementary materials for this article are available online.     

Australian demography at the millennium

This paper looks backwards over the last ten years to see what topics might concern Australian demographers in the future. The possibility of convergence or ’sameness’ is considered, but not proven. The main areas considered are historical demography, mortality, fertility, marriage, fertility regulation, internal migration, international migration, human resources, ageing, forecasting, the family life cycle, policy, and gender.     

Some remarks on the paper by A. Okore, 'Rural-urban fertility differentials in Southern Nigeria: An assessment of some available evidence'

Abstract In his paper Okore(1) critically examines the view of Olusanya and Ekanem that, partly because of shorter periods of breastfeeding and abstinence associated with 'modernization', urban fertility exceeds rural. Unfortunately, the proponents of this view have produced very few hard data on durations of breast-feeding and abstinence.(2).     

A neo-classical education transitions approach: A corrected tale for three cohorts

Analysts have regarded education transitions research as revealing late stage educational egalitarianism in the United States (e.g., Stolzenberg, 1994) and as sufficiently robust to guide policymakers (e.g., Hout, 2007). However, critics suggest parameter estimates are contaminated by selection bias (e.g., De Graaf & Ganzeboom, 1993), key parameter differences are unidentified (e.g., Cameron & Heckman, 1998), cross-transition comparisons are faulty, and the data are inappropriate. Useful modifications have been offered, (e.g., [Breen and Jonsson, 2000], [Hauser and Andrew, 2006] and [Lucas, 2001]), but analysts have yet to comprehensively address the challenges critics pose. In response, we propose a neo-classical education transitions approach that uses fuller sets of data and models that explicitly address the primary threats to proper inference. Using this approach we re-assess the educational attainment process for a baby boomer cohort, a Generation X cohort, and a Generation Y cohort. All cohorts fail to replicate the waning coefficients pattern. Methodologically, the study responds to criticisms in a way that offers methods for continued cross-national comparative research. Substantively, the study undermines confidence that standard education transitions research can provide policy guidance and the claim of late stage egalitarianism in the United States educational attainment process.     

Family Functioning and Its Relation to Parental Discipline

The Family Adaptability and Cohesion Scales (FACES) are one of the most used instruments in the study of family relations, assessing relevant dimensions of family functioning. This study aims to examine the relationship between cohesion, communication and family satisfaction, measured by FACES IV, and the dimensions of discipline inventory (DDI). The sample consisted of 380 subjects (190 adolescents and 190 parents). Fathers are the main users of physical discipline and boys are the main targets of most discipline practices. Regarding the association of the DDI and FACES, families with a balanced cohesion use less punitive discipline, families with enmeshed cohesion and families with disengaged cohesion have higher and less use of the analyzed disciplinary practices respectively. Considering the results, it may be useful to work together with families to promote the use of positive disciplinary methods and work their communication skills in order to improve cohesion and consequently family satisfaction.