Determinants of engagement in paid work following social security benefit receipt among older women

Work behavior among older men approaching or following retirement has received considerable research attention over the past two decades, but research on older women's work behavior is still in its incipient stage. Based on data from the 1982 New Beneficiary Survey (NBS) and the 1991 New Beneficiary Follow-up (NBF), this study analyzes the extent and determinants of employment among women who received their first Social Security benefits between 1980 and 1981. More than one fourth of the women continued to work or rejoined the labor force following their first Social Security benefit receipt. Financial need was found to be the primary reason for and the most significant determinant of women's continuing work or (re)entry into the labor force. But the level of education, health, spouse's work status, and previous work history were also found to be significant determinants of the likelihood and duration of their employment following Social Security receipt.     

Bootstrap confidence regions computed from autoregressions of arbitrary order

Given a linear time series, e.g. an autoregression of infinite order, we may construct a finite order approximation and use that as the basis for confidence regions. The sieve or autoregressive bootstrap, as this method is often called, is generally seen as a competitor with the better-understood block bootstrap approach. However, in the present paper we argue that, for linear time series, the sieve bootstrap has significantly better performance than blocking methods and offers a wider range of opportunities. In particular, since it does not corrupt second-order properties then it may be used in a double-bootstrap form, with the second bootstrap application being employed to calibrate a basic percentile method confidence interval. This approach confers second-order accuracy without the need to estimate variance. That offers substantial benefits, since variances of statistics based on time series can be difficult to estimate reliably, and—partly because of the relatively small amount of information contained in a dependent process—are notorious for causing problems when used to Studentize. Other advantages of the sieve bootstrap include considerably greater robustness against variations in the choice of the tuning parameter, here equal to the autoregressive order, and the fact that, in contradistinction to the case of the block bootstrap, the percentile t version of the sieve bootstrap may be based on the 'raw' estimator of standard error. In the process of establishing these properties we show that the sieve bootstrap is second order correct.     

Minimizing makespan in an ordered flow shop with?machine-dependent processing times

We consider a generalization of the proportionate flow shop problem with the makespan objective. Each job has a processing requirement and each machine has a characteristic value. In our case, we assume that the time a job occupies a machine is equal to the processing requirement of the job plus a setup time that is equal to the characteristic value of that machine. In this paper, we consider permutation schedules and show that the problem is solvable in polynomial time when the number of machines is fixed.     

Likelihood approach for evaluating bioequivalence of highly variable drugs

Bioequivalence (BE) is required for approving a generic drug. The two one‐sided tests procedure (TOST, or the 90% confidence interval approach) has been used as the mainstream methodology to test average BE (ABE) on pharmacokinetic parameters such as the area under the blood concentration‐time curve and the peak concentration. However, for highly variable drugs (%CV > 30%), it is difficult to demonstrate ABE in a standard cross‐over study with the typical number of subjects using the TOST because of lack of power. Recently, the US Food and Drug Administration and the European Medicines Agency recommended similar but not identical reference‐scaled average BE (RSABE) approaches to address this issue. Although the power is improved, the new approaches may not guarantee a high level of confidence for the true difference between two drugs at the ABE boundaries. It is also difficult for these approaches to address the issues of population BE (PBE) and individual BE (IBE). We advocate the use of a likelihood approach for representing and interpreting BE data as evidence. Using example data from a full replicate 2 × 4 cross‐over study, we demonstrate how to present evidence using the profile likelihoods for the mean difference and standard deviation ratios of the two drugs for the pharmacokinetic parameters. With this approach, we present evidence for PBE and IBE as well as ABE within a unified framework. Our simulations show that the operating characteristics of the proposed likelihood approach are comparable with the RSABE approaches when the same criteria are applied. Copyright © 2014 John Wiley & Sons, Ltd.     

What Affects the Happiness of Adopted Children in South Korea? Does the Adoption Matter to Their Happiness?

Child and Adolescent Social Work Journal - Since the ultimate goal of adoption is to provide children a happy life in a stable family environment, our major concern is children’s happiness...     

Static Numbers to Dynamic Statistics: Designing a Policy-Friendly Social Policy Indicator Framework

In line with the economic crisis and rapid socio-demographic changes, the interest in ??social?? and ??well-being?? indicators has been revived. Social indicator movements of the 1960s resulted in the establishment of social indicator statistical frameworks; that legacy has remained intact in many national governments and international organisations. With this background, this research examines whether existing social indicator frameworks are valid and effective enough to address increasingly complex social issues. The authors argue that, despite some improvements, current social indicators fail to provide an effective framework and tool for measuring the progress of social welfare and also for developing or reforming social policy to cope with newly emerging social problems. While proposing a new social indicator framework based on the Organisation for Economic Co-operation and Development??s pressure-state-response (PSR) model, the paper argues that the new framework should be more than displaying static numbers but should use dynamic statistics revealing causes and effects and shedding light on social and policy changes.     

The impact of newsroom changes and the rise of social media on the practice of media relations

Recent changes in American media have resulted in direct impacts on the work of PR professionals, from newsroom reductions in traditional media outlets to the rise of social media. This study examines changes in the media relations dynamic with qualitative, in-depth interviews from 12 PR professionals in a medium, eastern U.S. city. Findings include PR professionals doing less traditional media relations, mostly attributable to downsized newsrooms, and frustration with the resulting dearth of institutional knowledge, influx of young, inexperienced reporters, and shallow stories. While participants see opportunities to inject unfiltered messages in media, overall they value reporter relationships and using social media in communication with them and in their job. Although new media are seen as one more task on an already very full PR plate, participants acknowledge their importance and growing relevance. Overall, PR professionals see their and the industry's future including both traditional and new media.     

Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors

We establish consistency of posterior distribution when a Gaussian process prior is used as a prior distribution for the unknown binary regression function. Specifically, we take the work of Ghosal and Roy [2006. Posterior consistency of Gaussian process prior for nonparametric binary regression. Ann. Statist. 34, 2413–2429] as our starting point, and then weaken their assumptions on the smoothness of the Gaussian process kernel while retaining a stronger yet applicable condition about design points. Furthermore, we extend their results to multi-dimensional covariates under a weaker smoothness condition on the Gaussian process. Finally, we study the extent to which posterior consistency can be achieved under a general model where, when additional hyperparameters in the covariance function of a Gaussian process are involved.     

The Infrequency of Family Violence

We examined the frequency of domestic violence and verbal altercations relative to the level of domestic conflict using survey data from the United States and Korea. We found evidence that individuals are generally less likely to use violence during an altercation if the antagonist is a family member than if the antagonist is a stranger. People apparently have stronger inhibitions about hitting family members than about hitting strangers, and, as a result, domestic violence is infrequent relative to the level of domestic conflict. In addition, verbal altercations are more likely to occur in conflicts with partners and children than in conflicts involving strangers, suggesting that the relaxation of rules of politeness contributes to the expression of grievances and ultimately the use of violence in these relationships.     

Applicability of the Social Development Model to Urban Ethnic Minority Youth: Examining the Relationship between External Constraints,Family Socialization,and Problem Behaviors

The development of preventive interventions targeting adolescent problem behaviors requires a thorough understanding of risk and protective factors for such behaviors. However, few studies examine whether different cultural and ethnic groups share these factors. This study is an attempt to fill a gap in research by examining similarities and differences in risk factors across racial and ethnic groups. The social development model has shown promise in organizing predictors of problem behaviors. This article investigates whether a version of that model can be generalized to youth in different racial and ethnic groups (N=2,055, age range from 11 to 15), including African American (n=478), Asian Pacific Islander (API) American (n=491), multiracial (n=442), and European American (n=644) youth. The results demonstrate that common risk factors can be applied to adolescents, regardless of their race and ethnicity. The findings also demonstrate that there are racial and ethnic differences in the magnitudes of relationships among factors that affect problem behaviors. Further study is warranted to develop a better understanding of these differential magnitudes.