Solution Procedures for the Lot-Streaming Problem

Lot streaming is the process of splitting a job into sublots so its operations can be overlapped and its progress accelerated. We present a computationally efficient procedure for solving the m-machine, two-sublot problem, and we discuss the bottleneck insights that emerge from the analysis. We also examine heuristic approaches for more than two sublots and discuss computational results for these procedures.     

Will the ASA's Efforts to Improve Statistical Practice be Successful? Some Evidence to the Contrary

ABSTRACT

Recent efforts by the American Statistical Association to improve statistical practice, especially in countering the misuse and abuse of null hypothesis significance testing (NHST) and p-values, are to be welcomed. But will they be successful? The present study offers compelling evidence that this will be an extraordinarily difficult task. Dramatic citation-count data on 25 articles and books severely critical of NHST's negative impact on good science, underlining that this issue was/is well known, did nothing to stem its usage over the period 1960–2007. On the contrary, employment of NHST increased during this time. To be successful in this endeavor, as well as restoring the relevance of the statistics profession to the scientific community in the 21st century, the ASA must be prepared to dispense detailed advice. This includes specifying those situations, if they can be identified, in which the p-value plays a clearly valuable role in data analysis and interpretation. The ASA might also consider a statement that recommends abandoning the use of p-values.     

Zero-inflated sum of Conway-Maxwell-Poissons (ZISCMP) regression

While excess zeros are often thought to cause data over-dispersion (i.e. when the variance exceeds the mean), this implication is not absolute. One should instead consider a flexible class of distributions that can address data dispersion along with excess zeros. This work develops a zero-inflated sum-of-Conway-Maxwell-Poissons (ZISCMP) regression as a flexible analysis tool to model count data that express significant data dispersion and contain excess zeros. This class of models contains several special case zero-inflated regressions, including zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), zero-inflated binomial (ZIB), and the zero-inflated Conway-Maxwell-Poisson (ZICMP). Through simulated and real data examples, we demonstrate class flexibility and usefulness. We further utilize it to analyze shark species data from Australia's Great Barrier Reef to assess the environmental impact of human action on the number of various species of sharks.     

Quantile regression for large-scale data via sparse exponential transform method

In recent decades, quantile regression has received much more attention from academics and practitioners. However, most of existing computational algorithms are only effective for small or moderate size problems. They cannot solve quantile regression with large-scale data reliably and efficiently. To this end, we propose a new algorithm to implement quantile regression on large-scale data using the sparse exponential transform (SET) method. This algorithm mainly constructs a well-conditioned basis and a sampling matrix to reduce the number of observations. It then solves a quantile regression problem on this reduced matrix and obtains an approximate solution. Through simulation studies and empirical analysis of a 5% sample of the US 2000 Census data, we demonstrate efficiency of the SET-based algorithm. Numerical results indicate that our new algorithm is effective in terms of computation time and performs well for large-scale quantile regression.     

The exponentiated power exponential regression model with different regression structures: application in nursing data

We define the exponentiated power exponential distribution and propose a regression model with different systematic structures based on the new distribution. We show that the new regression model can be applied to dispersion data since it represents a parametric family of models that includes as sub-models some widely-known regression models. It then can be used more effectively in the analysis of real data. We use maximum likelihood estimation and derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. Some global-influence measurements are also investigated and simulation studies are performed to evaluate the accuracy of the estimates. We provide an application of the regression model with four systematic structures to nursing activities score data in the Unit of the Medical Clinic of University of São Paulo (USP) Hospital.     

Participation in Everyday Life Before and After a Housing Adaptation

Housing adaptation aims to enable clients to live independently in their own homes. Studies focusing on participation in everyday life following a housing adaptation are lacking and needed. This study aimed to explore housing adaptation clients' experiences of participation in everyday life before and after a housing adaptation, through the lens of a housing adaptation, using a qualitative follow-up design, with 11 participants. It was found that when the housing adaptation met the participants' needs, performance of activities improved and the housing adaptation opened doors to engagement and participation in everyday life. Thus, focus on performance and engagement in everyday life at the onset of the housing adaptation process, combined with regular follow-ups, may enhance participation.     

Que faut‐il voir dans les écarts de rémunération entre les travailleurs immigrés des pays du Golfe: l'effet d'a priori patronaux ou la simple conséquence de coûts d'opportunité différents?

Les auteurs s'intéressent aux disparités salariales entre les différents groupes de migrants qualifiés qui travaillent en grand nombre pour le secteur privé dans les États du Conseil de coopération du Golfe. Ils se demandent notamment si la prime salariale des Occidentaux (par rapport aux travailleurs venus d'Asie ou d'autres États arabes) découle d'éventuels a priori des employeurs. L'analyse, qui repose sur des données de 2012–2014 et sur deux méthodes de décomposition classiques, infirme l'hypothèse: les caractéristiques observables relatives à la productivité expliquent entre un tiers et trois quarts des écarts; le coût d'opportunité de la migration, supérieur pour les Occidentaux, explique la portion restante.     

Social Harmony in Hong Kong: Level,Determinants and Policy Implications

This study aims at ascertaining how Hong Kong people perceive Hong Kong as a harmonious society. It also identifies the elements that are most conducive to social harmony in Hong Kong, so that the government could take reference when formulating new policies. 1,062 adults residents were asked to rate their perceived level of social harmony and their satisfaction with 36 items (divided into three dimensions: public governance, society, and economy, family and work) for which the research team believes would be influencing the perceived level of social harmony. Results show that the average rating of social harmony was 5.57 (out of 10), delineating a moderate level of social harmony. Subsequent multivariate factor analysis and regression analysis show that the four extracted factors (from the three dimensions) had significant impacts on the level of social harmony. These were, in order of significance: (a) public governance, (b) social solidarity and respect, (c) economy/family/work and, (d) social tolerance and progressiveness. According to the factor loadings of each significant factor, we identified four core values which we hope the government would consider when formulating new policies, as follows: (1) A Justice Government with Sincerity on Communication, (2) Mutual Support and Respect with Integrity and Dedication, (3) Dedication to One’s Job and Community by Helping the Needed and, (4) Creativity and Progressiveness with Tolerance. Implications for policy making are discussed. The study was conducted under the direction and guidance of the Fostering Social Harmony Task Force of the Hong Kong Professionals and Senior Executives Association (HKPASEA). The authors acknowledge the kind support and assistance provided by the Council Members of HKPASEA and staff members of the Centre for Corporate Governance and Financial Policy at Hong Kong Baptist University. We are also grateful to Prof. Alex Michalos and Prof. P. K. Ip for their comments and suggestions given at the International Conference on National Well-Being held in November 2006 at the National Central University, Taiwan.