Comparing the U.S. Decennial Census Coverage Estimates for Children from Demographic Analysis and Coverage Measurement Surveys

Following every U.S. decennial census since 1960, the U.S. Census Bureau has evaluated the completeness of coverage using two different methods. Demographic analysis (DA) compares the census counts to a set of independent population estimates to infer coverage differences by age, sex, and race. The survey-based approach (also called dual system estimation or DSE) provides coverage estimates based on matching data from a post-enumeration survey to census records. This paper reviews the fundamentals of the two methodological approaches and then initially examines the results of these two methods for the 2010 decennial census in terms of consistency and inconsistency for age groups. The authors find that the two methods produce relatively consistent results for all age groups, except for young children. Consequently, the paper focuses on the results for children. Results of the 1990, 2000, and 2010 decennial censuses are shown for the overall population in this age group and by demographic detail (age, race, and Hispanic origin). Among children, the DA and DSE results are most inconsistent for the population aged 0–4 and most consistent for ages 10–17. Results also show that DA and DSE are more consistent for Black than non-Black populations. The authors discuss possible explanations for the differences in the two methods for young children and conclude that the DSE approach may underestimate the net undercount of young children due to correlation bias.     

Measuring disparities in access to water based on the normative content of the human right

Measuring access to water in the Sustainable Development Goals era involves taking into account the human rights framework. Therefore, its content should be considered to conceptualize the level of service through adequate indicators and to follow-up inequities reduction at global, national and local level. This research develops and tests a methodology to measure intra-community disparities based on human right to water normative criteria through a stratified sampling, splitting households served by community based organizations and those self-provided. This approach implies considering much reduced populations, thus special care needs to be taken with sample sizes and uncertainty of estimators. The proposed methodology is practical to locate and accurately characterize minority sectors within rural communities and allows moving beyond central-tendency estimators. It implies higher costs for field data collection than traditional approaches, but this can be assumed given the relevance of the approach from a human rights perspective, which calls for adequate tools for equity-oriented policy making at local level. The research point out how results might be used to shape decision-making processes.     

SCHEDULING PARALLEL PROCESSORS WITH SETUP COSTS AND RESOURCE LIMITATIONS

An integer linear programming model is presented for the scheduling of n products on m identical machines. The particular problem studied is one that occurs frequently in the fiberglass and textile industries. The model incorporates setup costs, lost production costs, and overtime costs. Due to the structure of the model, integer solutions can be obtained by explicitly restricting only a small number of the integer variables. This allows those responsible for scheduling to solve realistically sized problems in an efficient manner. Computational results are provided for a set of generated test problems.     

Machine Learning for Drug Overdose Surveillance

ABSTRACT

We describe two recently proposed machine learning approaches for discovering emerging trends in fatal accidental drug overdoses. The Gaussian Process Subset Scan (Herlands, McFowland, Wilson, & Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) enables early detection of emerging patterns in spatio-temporal data, accounting for both the complex, correlated nature of the data and the fact that detecting subtle patterns requires integration of information across multiple spatial areas and multiple time steps. We apply this approach to 17 years of county-aggregated data for monthly opioid overdose deaths in the New York City metropolitan area, showing clear advantages in the utility of discovered patterns as compared to typical anomaly detection approaches. To detect and characterize emerging overdose patterns that differentially affect a subpopulation of the data, including geographic, demographic, and behavioral patterns (e.g., which combinations of drugs are involved), we apply the Multidimensional Tensor Scan (Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) to 8 years of case-level overdose data from Allegheny County, Pennsylvania. We discover previously unidentified overdose patterns which reveal unusual demographic clusters, show impacts of drug legislation, and demonstrate potential for early detection and targeted intervention. These approaches to early detection of overdose patterns can inform prevention and response efforts, as well as understanding the effects of policy changes.     

New Price,New Hope? An Examination of the Effects of Doubling the Ticket Price in UK Lotto

The UK Lotto game was introduced in November 1994 with a standard 6/49 format and an entry fee of £1 per ticket. After several years, revenue began to fall despite extensive publicity and a variety of inducements. By 2013, nominal weekly revenue was less than half the 1995 level. In October 2013, the operator doubled the price of a ticket to £2 and made a number of changes to the pay-out structure of smaller prizes. The intent of the changes was to reverse the long downward trend in game revenue by encouraging higher jackpots and offering more pay-out opportunities for each ticket. We use draw by draw revenue and other data to evaluate how players responded to these changes and find that, while ticket sales fell dramatically, total revenue rose following the changes. Primarily this appears to have been the consequence of increased frequency of rollovers (and therefore of more frequent high jackpot draws) rather than ticket price inelasticity. However, although there was a short-term gain in revenue, the changes did not arrest, and indeed seem to have accentuated, the long-run trend decrease in the revenue generated by the game.     

互联网金融发展对中国经济增长影响的实证

文章从内生增长理论视角出发,在线性内生增长AK模型的基础上,将影响中国宏观经济增长的关键变量简化为资本边际产出率、储蓄-投资转换率和储蓄率,进而结合中国互联网金融发展指数以及中国2011-2015年的有关时间序列数据,对互联网金融发展指数和上述变量相关性进行实证研究,结果表明互联网金融的发展对上述变量均能产生正向影响,互联网金融的发展能够有效促进中国宏观经济的增长.     

The Moderating Effect of Living with a Child Before Incarceration on Postrelease Outcomes Related to a Prison-Based Parent Management Training Program

ABSTRACT

With the rapid growth in incarceration in the United States over the past few decades came dramatic growth in the number of the incarcerated parents with at least one minor child. Parental incarceration places extra stresses and strains on families and children. Almost all of those incarcerated will eventually be released. However, the majority of those released from prison will be rearrested within a year. Finding interventions that can decrease the likelihood of returning to crime and to incarceration are of utmost importance. Using a social bond theory framework, the authors examine the moderating effect of living with a child before incarceration on program outcomes related to a prison-based parent management training program. A significant effect was found. Implications for these findings are discussed for future research and practice.     

<Emphasis Type="BoldItalic">MAD-STEC</Emphasis>: a method for multiple automatic detection of space-time emerging clusters

Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev–Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil.     

Stepchildren’s Communicative and Emotional Journey from Divorce to Remarriage: Predictors of Stepfamily Satisfaction

This study explores the emotional and communicative profiles of young adults who have experienced a parental divorce and the emergence of a stepfamily to better understand influences on stepfamily satisfaction. Results of regression analyses indicate that strong negative emotions experienced at the time of the divorce are a negative predictor of current stepfamily satisfaction, even after controlling for age at the time of the divorce. In addition, level of open self-disclosure to a stepparent, although not parents, is a positive predictor of current stepfamily satisfaction. Finally, the extent to which the father has now fully explained the circumstances of the divorce is a positive predictor of current stepfamily satisfaction, whereas the extent to which mother has now fully explained the circumstances of the divorce is a negative predictor of current stepfamily satisfaction. These findings are discussed and future directions for research on stepfamily interaction and satisfaction are offered.