An Analytical Investigation of the Bullwhip Effect

The Bullwhip Effect is problematic: order variability increases as orders propagate along the supply chain. The fundamental differential delay equations for a retailer's inventory reacting to a surge in demand are solved exactly. Much of the rich and complex inventory behavior is determined by the replenishment delay. The analytical solutions agree with numerical integrations and previous control theory results. Managerially useful ordering strategies are proposed. Exact expressions are derived for the retailer's orders to the manufacturer, and the Bullwhip Effect arises naturally. The approach is quite general and applicable to a wide variety of supply chain problems.     

THE ROLE OF MARITAL STATUS IN HEALTH SERVICES EXPENDITURES FOR PSYCHIATRIC OUTPATTIENTS

This study tested the hypothesis that married psychiatric outpatients would have lower total health services expenditures than divorced or separated patients. Chart review of the 471 individuals attending an academic medical center outpatient psychiatric clinic during 1994 identified 131 married, 40 separated, and 93 divorced patients. Separated men had significantly higher average total charges ($16,890) than married ($5,279) or divorced ($5,539) men by one-way ANOVA (p < .05). The nonparametric Mann-Whitney test also showed that separated men had higher charges than married or divorced men. There were no differences between marital status groups for women.     

Distribution of Exposure Concentrations and Doses for Constituents of Environmental Tobacco Smoke

The ultimate goal of the research reported in this series of three articles is to derive distributions of doses of selected environmental tobacco smoke (ETS)-related chemicals for nonsmoking workers. This analysis uses data from the 16-City Study collected with personal monitors over the course of one workday in workplaces where smoking occurred. In this article, we describe distributions of ETS chemical concentrations and the characteristics of those distributions (e.g., whether the distribution was log normal for a given constituent) for the workplace exposure. Next, we present population parameters relevant for estimating dose distributions and the methods used for estimating those dose distributions. Finally, we derive distributions of doses of selected ETS-related constituents obtained in the workplace for people in smoking work environments. Estimating dose distributions provided information beyond the usual point estimate of dose and showed that the preponderance of individuals exposed to ETS in the workplace were exposed at the low end of the dose distribution curve. The results of this analysis include estimations of hourly maxima and time-weighted average (TWA) doses of nicotine from workplace exposures to ETS (extrapolated from 1 day to 1 week) and doses derived from modeled lung burdens of ultraviolet-absorbing particulate matter (UVPM) and solanesol resulting from workplace exposures to ETS (extrapolated from 1 day to 1 year).     

Using Mand Training to Establish an Echoic Repertoire in Young Children with Autism

The Analysis of Verbal Behavior - This research describes a method that initially establishes a mand repertoire as the first component in producing echoic and tact repertoires in young children...     

Statistical approaches for conducting network meta-analysis in drug development

We introduce health technology assessment and evidence synthesis briefly, and then concentrate on the statistical approaches used for conducting network meta-analysis (NMA) in the development and approval of new health technologies. NMA is an extension of standard meta-analysis where indirect as well as direct information is combined and can be seen as similar to the analysis of incomplete-block designs. We illustrate it with an example involving three treatments, using fixed-effects and random-effects models, and using frequentist and Bayesian approaches. As most statisticians in the pharmaceutical industry are familiar with SAS? software for analyzing clinical trials, we provide example code for each of the methods we illustrate. One issue that has been overlooked in the literature is the choice of constraints applied to random effects, and we show how this affects the estimates and standard errors and propose a symmetric set of constraints that is equivalent to most current practice. Finally, we discuss the role of statisticians in planning and carrying out NMAs and the strategy for dealing with important issues such as heterogeneity.     

Social work and the shadow father: lessons for engaging fathers in Northern Ireland

The legislative framework of social work practice has consistently highlighted the need to work in partnership with parents, with far‐reaching implications for families. However, the importance of engaging fathers in social work practice is an issue that has received limited attention within academic debate and research. A research study undertaken across six family centres, investigated paternal involvement in family centre social work in Northern Ireland. The study involved 46 semi‐structured interviews with social workers, fathers and mothers. This paper presents the views of 22 social workers on the barriers to paternal involvement in family centre interventions. A range of factors were identified which served to inhibit or promote engagement of fathers. There were substantially more deterrents than promoters, a clear indicator of the problematic nature of paternal involvement. The findings highlight that both attitudes and practices of social workers influence the engagement of fathers. Recommendations drawn from the findings are presented for the development of father – inclusive social work practices and research.     

Hybrid-based confidence intervals for the ratio of two treatment means in the over-dispersed Poisson data

In many clinical trials and epidemiological studies, comparing the mean count response of an exposed group to a control group is often of interest. This type of data is often over-dispersed with respect to Poisson variation, and previous studies usually compared groups using confidence intervals (CIs) of the difference between the two means. However, in some situations, especially when the means are small, interval estimation of the mean ratio (MR) is preferable. Moreover, Cox and Lewis [4 D.R. Cox and P.A.W. Lewis, The Statistical Analysis of Series of Events, Methuen, London, 1966.[Crossref] , [Google Scholar]] pointed out many other situations where the MR is more relevant than the difference of means. In this paper, we consider CI construction for the ratio of means between two treatments for over-dispersed Poisson data. We develop several CIs for the situation by hybridizing two separate CIs for two individual means. Extensive simulations show that all hybrid-based CIs perform reasonably well in terms of coverage. However, the CIs based on the delta method using the logarithmic transformation perform better than other intervals in the sense that they have slightly shorter interval lengths and show better balance of tail errors. These proposed CIs are illustrated with three real data examples.     

Determinants of Interoutsourcing: An Analytical Approach

Interoutsourcing is a round‐way process in which the vendor is its customer's customer and the customer is its vendor's vendor. While interoutsourcing is emerging as a prominent outsourcing strategy in many industries, there are no rigorous analytical studies focusing on this mechanism. In this article, we analytically demonstrate the efficacy of interoutsourcing by comparing it with normal outsourcing. Our results show that, compared with normal outsourcing, interoutsourcing acts as a self‐enforcer of vendor firms' behaviors toward increasing outsourcing service value. However, in situations where there is a mismatch of outsourcing activities, a high degree of incentive that is based on outsourcing service value, and a high cost of capital, interoutsourcing is not preferred to normal outsourcing. We discuss these results in detail and provide managerial implications for firms involved in interoutsourcing decisions.     

Reversible jump methods for generalised linear models and generalised linear mixed models

A reversible jump algorithm for Bayesian model determination among generalised linear models, under relatively diffuse prior distributions for the model parameters, is proposed. Orthogonal projections of the current linear predictor are used so that knowledge from the current model parameters is used to make effective proposals. This idea is generalised to moves of a reversible jump algorithm for model determination among generalised linear mixed models. Therefore, this algorithm exploits the full flexibility available in the reversible jump method. The algorithm is demonstrated via two examples and compared to existing methods.