Developing a Data-driven Approach to inform Planning in County Health and Human Services Departments in the Context of a Case Study on Obesity

Since the 1970s, the obesity rate has steadily increased due to growing availability of food and declining physical activity. The existing environments within a community, including active recreation opportunities, access to healthy food options, the built environment, and transportation options, can moderate obesity. In Virginia, Fairfax County Health and Human Services (HHS) system is interested in developing the capacity for data-driven approaches to gain insights on current and future issues, such as obesity, to characterize factors at the county and sub-county level, and to use these insights to inform policy options. In exploring these questions, we developed statistical methods to combined data from a multitude of different sources including local administrative data (e.g., tax assessments, land use, student surveys), place-based data, and federal collections. Using synthetic data methods based on imputation, we recomputed American Community Survey statistics for non-Census tract geographic regions for political districts and high school attendance areas. We combined this with environmental factors, such as land dedicated to parks and recreation facilities, as well as measures of the density of healthy and unhealthy food locations to create a map of potentially obesogenic factors. Finally, we combined these data sources with Fairfax County’s youth survey and trained a random forest model to predict the effects of the environment on healthy food consumption and exercise. Our analysis highlights the need for (administrative) data at a fine scale and recommends policy changes concerning the recording and sharing of local data to better inform the policy and program development

Using a Remote Access Data Enclave for Data Dissemination

This article describes the approach taken by NORC and NIST to provide remote researcher access to confidential business micro data. We have combined technical, legal and organizational approaches to protect respondent confidential. We have also instituted a number of technical approaches to encourage researchers to provide metadata documentation

Our Moon in a new light

Content and activities about studying the Moon's spectrum. Front: Grade 6-9 students. Back: Educators of grades 6-9.Content development Stephanie Shipp and Christine Shupla ; scientific oversight, Allan Treiman, David Kring, and Walter Kiefer ; graphic design Leanne Woolley.Back panels: What is Electromagnetic Radiation? -- How do Scientists Determine the Composition of Rocks They Can't Touch? -- Spectrometers in Action Around the Moon -- Exploration Timeline -- Meet a Lunar Geologist, Dr. Carle Pieters, Brown University -- Try This! Seeing the Invisible -- Share a Story -- Further Exploration, Books, Websites, Classroom Resources

Leveraging U.S. Army Administrative Data for Individual and Team Performance

The Army possesses vast amounts of administrative (archival) data about Soldiers. These data sources include screening tests, personnel action codes, training scores, global assessments, physical fitness scores, and more. However, the Army has yet to integrate these data to create a holistic operating picture. Our research focuses on repurposing Army administrative data to (1) operationalize social constructs of interest to the Army (e.g., Army Values, Warrior Ethos) and (2) model the predictive relationship between these constructs and individual (i.e., Soldier) and team (i.e., unit) performance and readiness. The goal of the project is to provide people analytics models to Army leadership for the purposes of optimizing human capital management decisions. Our talk will describe the theoretical underpinnings of our human performance model, drawing on disciplines such as social and industrial/organizational psychology, as well as our experience gaining access to and working with Army administrative data sources. Access to the archival administrative data is provided through the Army Analytics Group (AAG), Person-event Data Environment (PDE). The PDE is a business intelligence platform that has two central functions: (1) to provide a secure repository for data sources on U.S. military personnel; and (2) to provide a secure collaborative work environment where researchers can access unclassified but sensitive military data

Feature selection using Haar wavelet power spectrum

BACKGROUND: Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets. The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum. RESULTS: Haar wavelet power spectra of genes were analysed and it was observed to be different in different diagnostic categories. This difference in trend and magnitude of the spectrum may be utilized in gene selection. Most of the genes selected by earlier complex methods were selected by the very simple present method. Each earlier works proved only few genes are quite enough to approach the classification problem [1]. Hence the present method may be tried in conjunction with other classification methods. The technique was applied without removing the noise in data to validate the robustness of the method against the noise or outliers in the data. No special softwares or complex implementation is needed. The qualities of the genes selected by the present method were analysed through their gene expression data. Most of them were observed to be related to solve the classification issue since they were dominant in the diagnostic category of the dataset for which they were selected as features. CONCLUSION: In the present paper, the problem of feature selection of microarray gene expression data was considered. We analyzed the wavelet power spectrum of genes and proposed a clustering and feature selection method useful for classification based on Haar wavelet power spectrum. Application of this technique in this area is novel, simple, and faster than other methods, fit for a wide range of data types. The results are encouraging and throw light into the possibility of using this technique for problem domains like disease classification, gene network identification and personalized drug design

note: Inequality and the business cycle: A consumption viewpoint

Using Consumer Expenditure Survey data, we obtain summary measures of the distributions of income and consumption for each quarter between 1980 and 1994. We find that the trends in the distribution of income and consumption and the response of these trends to changes in inflation and unemployment were similar during this period. We find that unemployment does not significantly affect the inequality measures and that inflation has a progressive effect, i.e., that a decrease in inflation is associated with an increase in inequality. Finally, we find that the relationship between inequality and macroeconomic variables during the 1990s may be similar to the relationship that existed prior to 1980.Inequality · consumption · inflation · unemployment

Factors Affecting the Speed and Dissemination of Technology Transferred from the Federal Laboratories

Atlanta Conference on Science and Innovation Policy 2011This paper describes a study of the current state of affairs in technology transfer and commercialization at the U.S. federal intramural laboratories.The study began with a literature review that informed the approach to discussions with technology transfer personnel at federal agencies and laboratories, which served as the primary mode of data collection. Discussions were held with stakeholders from 12 agencies and 28 laboratories as well as over 30 other organizations.This paper identifies six factors that interviewees stated were affecting the speed and dissemination of technologies from federal laboratories to the private sector.Where applicable, comparisons to past literature on federal laboratory technology transfer are made. The paper also presents the issues around defining and measuring technology transfer success at the federal laboratories, strategies that laboratories are currently employing that may be useful for others to implement, and it ends with a discussion of areas in need of further study.Department of Commerc