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.     

Two-stage proportionate flexible flow shop to minimize the makespan

We consider a two-stage flexible flow shop problem with a single machine at one stage and m identical machines at the other stage, where the processing times of each job at both stages are identical. The objective is to minimize the makespan. We describe some optimality conditions and show that the problem is NP-hard when m is fixed. Finally, we present an approximation algorithm that has a worst-case performance ratio of $\frac{5}{4}$ for m=2 and $\frac{\sqrt{1+m^{2}}+1+m}{2m}$ for m≥3.     

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.     

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.     

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.     

Active Ageing Index in Korea – Comparison with China and EU countries

The evidence‐based policymaking relies on the use and robustness of the available data. Many conceptual and operational difficulties restrict this process, not least in making use of evidence to identify policy priorities. The Active Ageing Index (AAI), developed originally for the 28 European Union countries, offers a strong motivation in this respect. This paper reports on the development of the AAI for Korea, a country where speed and level of population aging is among the highest in the world. Drawing on the comparative analysis of the AAI results for Korea, China, and European countries, we find that Korea's AAI (35.3) is higher than the average of the AAI for all EU countries (33.9) but lower than China (37.3). Fitting Korea into the overall ranking with the EU countries and China (ranked 7), Korea is ranked 11, just behind Germany (10). The AAI results in Korea show that the employment domain performs extremely well compared with the EU countries, but other domains, especially “Social participation” and “Independent, healthy and secure living,” are achieving less favorable outcomes. High employment among the current cohorts of older workers in Korea can be attributed largely to the constraints of low pension income status.     

Testing non-nested log-linear models with pseudo estimator

As the number of random variables for the categorical data increases, the possible number of log-linear models which can be fitted to the data increases rapidly, so that various model selection methods are developed. However, we often found that some models chosen by different selection criteria do not coincide. In this paper, we propose a comparison method to test the final models which are non-nested. The statistic of Cox (1961, 1962) is applied to log-linear models for testing non-nested models, and the Kullback-Leibler measure of closeness (Pesaran 1987) is explored. In log-linear models, pseudo estimators for the expectation and the variance of Cox's statistic are not only derived but also shown to be consistent estimators.     

What makes hybrid insourcing successful: A new public–private partnership model for social welfare services

Outsourcing has been a key policy tool for delivering a range of social services, and regarded as more effective than insourcing or direct government provision. At the same time, it has also caused many delivery issues such as principal‐agent problems, a lack of policy coordination, and poor‐quality welfare services. While the pendulum continues to swing between insourcing and outsourcing, we aim to propose a new public–private partnership model called the “hybrid insourcing model” and examine which factors influence the performance of the model. In South Korea, around 2010, the local government in Namyangju City was the first to implement the “Hope Care Center model,” a kind of hybrid insourcing model, which has been praised for its innovation and widely emulated by central and local governments. Our analysis utilizes data collected between December 2017 and January 2018 from public sector employees and civilian staff in Namyangju and a comparable city, A. From this, we draw a number of implications, both for theory and for policy. We argue that, for public–private partnerships, active cooperation and equality are the biggest factors in contributing to positive performance. These work alongside leaders with a clear vision and with employees' positive attitude.     

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.