The role of public health in population health

The role of public health is central in population health. What distinguishes public health from clinical medicine is that it's focus is on the entire population--not the individual patient. To achieve the goal of population health, healthy communities, or Healthy People 2000 requires physician leadership in medicine and public health at all levels--local, state, and national. The challenge is formidable, but the goals are attainable through strategies that focus on the goal of the common good and through collaboration of public health, medicine, and the community.     

CONVERGENCE AND PREDICTION OF PRINCIPAL COMPONENT SCORES IN HIGH-DIMENSIONAL SETTINGS

A number of settings arise in which it is of interest to predict Principal Component (PC) scores for new observations using data from an initial sample. In this paper, we demonstrate that naive approaches to PC score prediction can be substantially biased towards 0 in the analysis of large matrices. This phenomenon is largely related to known inconsistency results for sample eigenvalues and eigenvectors as both dimensions of the matrix increase. For the spiked eigenvalue model for random matrices, we expand the generality of these results, and propose bias-adjusted PC score prediction. In addition, we compute the asymptotic correlation coefficient between PC scores from sample and population eigenvectors. Simulation and real data examples from the genetics literature show the improved bias and numerical properties of our estimators.     

Joint impact of multiple observations on a subset of variables in multiple linear regression

In multiple linear regression analysis, each observation affects the fitted regression equation differently and has varying influences on the regression coefficients of the different variables. Chatterjee & Hadi (1988) have proposed some measures such as DSSE_ij (Impact on Residual Sum of Squares of simultaneously omitting the ith observation and the jth variable), F_j (Partial F-test for the jth variable) and F_j(i) (Partial F-test for the jth variable omitting the ith observation) to show the joint impact and the interrelationship that exists among a variable and an observation. In this paper we have proposed more extended form of those measures DSSE_IJ, F_J and F_J(I) to deal with the interrelationships that exist among the multiple observations and a subset of variables by monitoring the effects of the simultaneous omission of multiple variables and multiple observations.     

A hierarchical model for extreme wind speeds

Summary.  A typical extreme value analysis is often carried out on the basis of simplistic inferential procedures, though the data being analysed may be structurally complex. Here we develop a hierarchical model for hourly gust maximum wind speed data, which attempts to identify site and seasonal effects for the marginal densities of hourly maxima, as well as for the serial dependence at each location. A Gaussian model for the random effects exploits the meteorological structure in the data, enabling increased precision for inferences at individual sites and in individual seasons. The Bayesian framework that is adopted is also exploited to obtain predictive return level estimates at each site, which incorporate uncertainty due to model estimation, as well as the randomness that is inherent in the processes that are involved.     

Multiracial Identity Integration: Perceptions of Conflict and Distance among Multiracial Individuals

This article examines how multiracial individuals negotiate their different and sometimes conflicting racial identities. Drawing from previous work on bicultural identity integration (see   Benet-Martínez & Haritatos, 2005 ), we proposed a new construct, multiracial identity integration (MII), to measure individual differences in perceptions of compatibility between multiple racial identities. We found that MII is composed of two independent subscales: racial distance that describes whether different racial identities are perceived as disparate, and racial conflict that describes whether different racial identities are perceived as in conflict. We also found that recalling positive multiracial experiences increased MII, while recalling negative multiracial experiences decreased MII. These findings have implications for understanding the psychological well-being of multiracial individuals, and the development of social policy and programs catered to this population.     

Relationships between Economics,Welfare, Social Network Factors,and Net Migration in the United States

By using economics, welfare and social network factors as frames of reference, this study aims to explore the relationship between these three factors and net migration to various US states. Adopting related variables collected from official aggregate data, this study first utilizes Logit Regression analysis to draw out seven variables that best explain net migration to the various states, then employs these variables in LISREL analyses to build a model explaining the factors influencing net migration to the various US states. Concretely, this research obtained the following findings: (1) the seven variables ‐‐ the average rate of net migrants of 2002–2005, Medicaid, federal aid, employment rate, non‐poverty population rate, and SSI subsidy ‐‐ all significantly affected (p < 0.01 or p < 0.05) net migration in 2006; (2) the main influences on net migration for the various states are, from highest to lowest, social network, economic, and welfare factors. More specifically, a better explanation is that, through the social network factor, economic and welfare factors exert an increased influence on the net number of migrants; and (3) as for the influence of social network factors on the number of net migrants, the social network factor for the previous year was found to best explain domestic migration flows, while the social network factor for the previous three‐to‐four years best explained international migration flows.     

Developing From Tranditional Microscale Chemistry to Microscale Green Chemistry

Microscale chemistry is appealing to all levels of education.In contrast to conventional macroscale chemistry,only minute amount of chemicals are required to undertaking a chemical investigation.     

Frailty modelling approaches for semi-competing risks data

Lifetime Data Analysis - In the semi-competing risks situation where only a terminal event censors a non-terminal event, observed event times can be correlated. Recently, frailty models with an...