Robust estimation of the ratio of scale parameters for positive random variables

An estimator of the ratio of scale parameters of the distributions of two positive random variables is developed for the case where the only difference between the distributions is a difference in scale. Simulation studies demonstrate that the estimator performs much better, in terms of mean squared error, than the most popular one among those estimators currently available.     

Fitting a Semi-Parametric Mixture Model for Competing Risks in Survival Data

A model for survival analysis is studied that is relevant for samples which are subject to multiple types of failure. In comparison with a more standard approach, through the appropriate use of hazard functions and transition probabilities, the model allows for a more accurate study of cause-specific failure with regard to both the timing and type of failure. A semiparametric specification of a mixture model is employed that is able to adjust for concomitant variables and allows for the assessment of their effects on the probabilities of eventual causes of failure through a generalized logistic model, and their effects on the corresponding conditional hazard functions by employing the Cox proportional hazards model. A carefully formulated estimation procedure is presented that uses an EM algorithm based on a profile likelihood construction. The methods discussed, which could also be used for reliability analysis, are applied to a prostate cancer data set.     

Alternating event processes during lifetimes: population dynamics and statistical inference

In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes.     

COMBINING HOUSEHOLD SURVEYS USING MASS IMPUTATION TO ESTIMATE POPULATION TOTALS

Pressure is often placed on statistical analysts to improve the accuracy of their population estimates. In response to this pressure, analysts have long exploited the potential to combine surveys in various ways. This paper develops a framework for combining surveys when data items from one of the surveys is mass imputed. The estimates from the surveys are combined using a composite estimator (CE). The CE accounts for the variability due to the imputation model and the surveys’ sampling schemes. Diagnostics for the validity of the imputation model are also discussed. We describe an application of combining the Australian Labour Force Survey and the National Aboriginal and Torres Strait Islander Health Survey to estimate employment characteristics about the Indigenous population. The findings suggest that combining these surveys is beneficial.     

自然与文化:悲观哲学经验

人存在于自然之中,但人不是一般意义上的自然之物,因为人拒绝接受肉体腐烂后思想的荒芜,于是,人开始对自身存在的价值进行深度思考,其结果是,人拒绝承认自己和动植物具有相同的属性,因为人既是自然之子,也是文化的产物。只有当人的精神发展从意识自己是种群的组成部分返回到意识自己作为个体存在的价值和意义之时,文化的作用才有可能发生。人类的发展伴随着野蛮的状态,也伴随着对命运一词的不断认识。人的伟大之处在于能够意识到死亡的不可避免,但同时在文化的帮助下去克服死亡的恐惧,最后让死亡成为有意义的文化事件。     

‘In a perfect world it would be great if they didn't exist’: How Australians experience payday loans

In the last few decades, payday lending has mushroomed in many developed countries. The arguments for and against an industry which provides small, short‐term loans at very high interest rates have also blossomed. This article presents findings from an Australian study to contribute to the international policy and practice debate about a sector which orients to those on a low income. At the heart of this debate lies a conundrum: Borrowing from payday lenders exacerbates poverty, yet many low‐income households rely on these loans. We argue that the key problem is the restricted framework within which the debate currently oscillates. Key Practitioner Message: ● Framing payday borrowing as a problem of market failure leads to one‐sided and ineffective regulatory responses; ● Until governments instigate real alternatives for cheap and readily available credit, and broader anti‐poverty measures, curbing access to payday lenders can have the perverse effect of increasing privation; ● For practitioners seeking to abolish payday lending, campaigns for higher wages and a liveable social welfare income are central.     

A comparison of six methods of analysing row-column designs with inter-block information

Six methods of obtaining estimates of treatment effects in a row-column design are considered. Five methods use estimates of inter-row and inter-column variation, and the remaining method is Ordinary Least Squares. Using simulation, these methods are examined to see which are most appropriate for minimising the sum of the squared differences between the estimates of the elementary treatment contrasts and their true values. Recommendations are made of which methods to use.     

Individual Prior Information in a Physiological Model of 2H8-Toluene Kinetics: An Empirical Bayes Estimation Strategy

Physiologically-based toxicokinetic (PBTK) models are widely used to quantify whole-body kinetics of various substances. However, since they attempt to reproduce anatomical structures and physiological events, they have a high number of parameters. Their identification from kinetic data alone is often impossible, and other information about the parameters is needed to render the model identifiable. The most commonly used approach consists of independently measuring, or taking from literature sources, some of the parameters, fixing them in the kinetic model, and then performing model identification on a reduced number of less certain parameters. This results in a substantial reduction of the degrees of freedom of the model. In this study, we show that this method results in final estimates of the free parameters whose precision is overestimated. We then compared this approach with an empirical Bayes approach, which takes into account not only the mean value, but also the error associated with the independently determined parameters. Blood and breath ²H₈-toluene washout curves, obtained in 17 subjects, were analyzed with a previously presented PBTK model suitable for person-specific dosimetry. Model parameters with the greatest effect on predicted levels were alveolar ventilation rate Q_PC, fat tissue fraction V_FC, blood-air partition coefficient K_b, fraction of cardiac output to fat Q_a/co and rate of extrahepatic metabolism V_max-p. Differences in the measured and Bayesian-fitted values of Q_PC, V_FC and K_b were significant (p < 0.05), and the precision of the fitted values V_max-p and Q_a/co went from 11 ± 5% to 75 ± 170% (NS) and from 8 ± 2% to 9 ± 2% (p < 0.05) respectively. The empirical Bayes approach did not result in less reliable parameter estimates: rather, it pointed out that the precision of parameter estimates can be overly optimistic when other parameters in the model, either directly measured or taken from literature sources, are treated as known without error. In conclusion, an empirical Bayes approach to parameter estimation resulted in a better model fit, different final parameter estimates, and more realistic parameter precisions.     

Optimal Purchase and Transportation Cost Lot Sizing for a Single Item

A review of the literature indicates that the traditional approach for evaluating quantity discount offerings for purchased items has not adequately considered the effect that transportation costs may have on the optimal order quantity; despite the general fact that purchased materials must bear transportation charges. The transportation cost structure for less-than-truckload (LTL) shipments reflects sizable reductions in freight rates when the shipment size exceeds one of the nominal rate breakpoints. However, the shipper must also be aware of the opportunity to reduce total freight costs by artificially inflating the actual shipping weight to the next rate breakpoint, in order that a lower marginal tariff is achieved for the entire shipment. Such over-declared shipments result in an effective freight rate schedule that is characterized by constant fixed charge segments in addition to the nominal marginal rates. Over-declared shipments are economical when the shipment volume is less than the rate breakpoint, but greater than a cost indifference point between the two adjacent marginal rates. This paper presents a simple analytical procedure for finding the order quantity that minimizes total purchase costs which reflect both transportation economies and quantity discounts. After first solving for the series of indifference points that apply to a particular freight rate schedule, a total purchase cost expression is presented that properly accounts for the actual transportation cost structure. The optimal purchase order quantity will be one of the four following possibilities: (1) the valid economic order quantity (EOQ), QC; (2) a purchase price breakpoint in excess of QC; (3) a transportation rate breakpoint in excess of QC; and (4) a modified EOQ which provides an over-declared shipment in excess of QC. Finally, an algorithm which systematically explores these four possibilities is presented and illustrated with a numerical example.     

Social Justice,Research, and Adolescence

In what ways might research on adolescence contribute to social justice? My 2014 Presidential Address identified strategies for social justice in our field. First, we need research that is conscious of biases, power, and privilege in science, as well as in our roles as scholars. Second, we need research that attends to inequities in lives of adolescents, and as scholars we need to question the ways that our research may unwittingly reinforce those inequalities. Third, we need research that attends to urgencies, that is, issues or conditions that influence adolescents’ well‐being which demand attention and action. I draw from a range of concepts and theoretical perspectives to make the case for a framework of social justice in research on adolescence.