A modified common factor model for modelling mortality jointly for both sexes

Journal of Population Research - There is an increasing attention on the joint modelling of multiple populations. Populations are related in several ways, such as neighbouring countries, females...     

The Gendered Nature of Managerial Discourse: the Case of a Local Authority

This paper is a response to organizational analysis which highlights the significance of discursive processes in the formation of occupational gender identity. A recurrent weakness in many of these accounts is their focus on the simple dualisms which structure gendered discourse. This tendency is often associated with the abstraction of debate from specific organizational settings. I aim therefore to address the question of the gendered nature of managerial discourse with reference to a case study of a local authority under restructuring. I argue here that the gendered nature of managerial discourse has to be seen as particularly complex, given the way in which it incorporates both ‘feminine’ and ‘masculine’ identities within an overarching managerial ethos, which is itself related to wider hegemonic projects.     

A simple procedure for the selection of significant effects

Summary.  Given a large number of test statistics, a small proportion of which represent departures from the relevant null hypothesis, a simple rule is given for choosing those statistics that are indicative of departure. It is based on fitting by moments a mixture model to the set of test statistics and then deriving an estimated likelihood ratio. Simulation suggests that the procedure has good properties when the departure from an overall null hypothesis is not too small.     

Robustness of testing the equality of two slopes in simple linear structural relationships

The usual test of the equality of two slopes in a simple structural relation-ship is the test formed from the normal approximation using the Fisher information matrix, assuming two explanatory variables are independent. This paper examines the robustness if the explanatory variables are, in fact, dependent. A more efficient estimator is derived for a matched pair situation.     

Portmanteau test for conditional heteroscedasticity, using ranks of squared residuals

Squared residual autocorrelations have been found useful in detecting departures from linearity in time series models. This is especially the case with data exhibiting heterogeneity in variances. A rank test is proposed which is much more robust than its parametric counterpart.     

Estimating large-scale general linear and seemingly unrelated regressions models after deleting observations

A new numerical method to solve the downdating problem (and variants thereof), namely removing the effect of some observations from the generalized least squares (GLS) estimator of the general linear model (GLM) after it has been estimated, is extensively investigated. It is verified that the solution of the downdated least squares problem can be obtained from the estimation of an equivalent GLM, where the original model is updated with the imaginary deleted observations. This updated GLM has a non positive definite dispersion matrix which comprises complex covariance values and it is proved herein to yield the same normal equations as the downdated model. Additionally, the problem of deleting observations from the seemingly unrelated regressions model is addressed, demonstrating the direct applicability of this method to other multivariate linear models. The algorithms which implement the novel downdating method utilize efficiently the previous computations from the estimation of the original model. As a result, the computational cost is significantly reduced. This shows the great usability potential of the downdating method in computationally intensive problems. The downdating algorithms have been applied to real and synthetic data to illustrate their efficiency.     

Efficient heterogeneous sampling for stochastic simulation with an illustration in health care applications

In modeling disease transmission, contacts are assumed to have different infection rates. A proper simulation must model the heterogeneity in the transmission rates. In this article, we present a computationally efficient algorithm that can be applied to a population with heterogeneous transmission rates. We conducted a simulation study to show that the algorithm is more efficient than other algorithms for sampling the disease transmission in a subset of the heterogeneous population. We use a valid stochastic model of pandemic influenza to illustrate the algorithm and to estimate the overall infection attack rates of influenza A (H1N1) in a Canadian city.     

Assessing Participation and Effectiveness of the Peer-Led Approach in Youth Sexual Health Education: Systematic Review and Meta-Analysis in More Developed Countries

Sexual health education for young people is crucial not only for development of norms but also for protection against vulnerabilities during this stage in life. Although several systematic reviews have examined the effectiveness of peer-led sex education, none have focused on the extent of peer participation. The purpose of this review was to evaluate peer-led sexual health education interventions in more developed countries (MDCs). Electronic and manual searches across five social science, education, and medical databases were conducted. Fifteen articles were selected in total. Most (10 of 15) studies gave low or no responsibility to peers. The majority of articles found improvements in sexual health knowledge (13 of 14) and attitudes (11 of 15) at postintervention stages. Two studies showed improved self-efficacy, and three showed behavioral changes. A preliminary synthesis of effectiveness and level of participation was done. Meta-analysis revealed a large effect on knowledge change (Hedges’ g = 0.84, 95% confidence interval [CI]: 0.43 to 1.25) and a medium effect on attitude change (Hedges’ g = 0.49, 95% CI: 0.19 to 0.80). Peer-led interventions could be a powerful tool. This review shows that this approach is effective in changing knowledge and attitudes but not behaviors. Further research and action are needed to understand optimal implementation.