In Search of the Optimum Harvey Wallbanger Recipe via Mixture Experiment Techniques

A Harvey Wallbanger is an alcoholic drink composed of three ingredients: orange juice, vodka, and Galliano. One of the authors (Sahrmann), a connoisseur of the libation, was perplexed upon discovering that different bartender handbooks listed different recipes for the drink. Determined to shed some light on this irksome problem, he issued invitations for an evening workshop session (party) to former and current attendees of an experimental-design training course taught within his company. A mixture experiment was designed and data collected using the class participants. This article describes the experimental design and the analysis of the data. The results of the experiment indicate that reducing the proportion of vodka produces better-flavored drinks. The results of the experiment were not entirely conclusive, however, so recommendations are made for future experimentation.     

Time Series Models for Count or Qualitative Observations

Time series sometimes consist of count data in which the number of events occurring in a given time interval is recorded. Such data are necessarily nonnegative integers, and an assumption of a Poisson or negative binomial distribution is often appropriate. This article sets ups a model in which the level of the process generating the observations changes over time. A recursion analogous to the Kalman filter is used to construct the likelihood function and to make predictions of future observations. Qualitative variables, based on a binomial or multinomial distribution, may be handled in a similar way. The model for count data may be extended to include explanatory variables. This enables nonstochastic slope and seasonal components to be included in the model, as well as permitting intervention analysis. The techniques are illustrated with a number of applications, and an attempt is made to develop a model-selection strategy along the lines of that used for Gaussian structural time series models. The applications include an analysis of the results of international football matches played between England and Scotland and an assessment of the effect of the British seat-belt law on the drivers of light-goods vehicles.     

When the Learning Disabled Go to College

Abstract

During the last decade, federal laws have provided for remedial education in elementary and secondary schools for students with learning disabilities, preparing large numbers of them for college. Federal law also mandates helping learning-disabled students with their needs once they matriculate. Declining numbers of high school graduates in the aftermath of the baby boom have made more colleges open their doors to these students. The disabilities, and the accommodations they require, arrive in college with the rest of a student's baggage, demanding attention. Colleges and universities have chosen a variety of approaches, from specific remedial programs and individual accomodations according to need to more general programs. Some colleges pretend these disabilities do not exist and seem oblivious to their presence on campus. Learning disabilities can have an impact in every class and lecture hall and can contribute to unhappiness and the college's attrition rate. On the other hand, responsive and responsible programs provide students with the resources for the same education, honors, and opportunities as their nondisabled peers.     

Statistics in Latin America

Statistics is a relatively new discipline in Latin America. At present only sparse information is available about the state of the statistical profession in Latin America. We present and summarize the available information about the job market; training, education, and research; professional societies and their activities; and so forth. We also share our hopes, concerns, and suggestions for the future.     

A Quality Risk Management Model Approach for Cell Therapy Manufacturing

International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell‐based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator‐introduced variations, and affected by heterogeneity of the processed organs/tissues and lot‐dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell‐based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo‐quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed.     

Symbols Build Communication and Thought: The Role of Gestures and Words in the Development of Engagement Skills and Social‐emotional Concepts during Toddlerhood

Social skills and symbol skills are positively associated in middle childhood, but the relation between these domains is less clear in newly verbal toddlers. Vygotsky proposed that symbols are both tools for interaction and mental tools for thought. Do symbols help even very young children build skills for interacting with and conceptualizing the social world? Longitudinal data from 108 children and mothers were collected when children were 14, 24, and 36 months. Children's gestures and words during mother–child interactions were used as symbol skill indicators to predict children's abilities to engage others and the number of social‐emotional concepts children portray during play. In a series of growth models, words had a stronger effect on engagement skills whereas early gesture use predicted later development of social‐emotional concepts. Therefore, even in early development, symbols serve as both communication tools and mental tools to construct understanding of the social‐emotional world.     

Prediction based classification for longitudinal biomarkers

Assessment of circulating CD4 count change over time in HIV-infected subjects on antiretroviral therapy (ART) is a central component of disease monitoring. The increasing number of HIV-infected subjects starting therapy and the limited capacity to support CD4 count testing within resource-limited settings have fueled interest in identifying correlates of CD4 count change such as total lymphocyte count, among others. The application of modeling techniques will be essential to this endeavor due to the typically non-linear CD4 trajectory over time and the multiple input variables necessary for capturing CD4 variability. We propose a prediction based classification approach that involves first stage modeling and subsequent classification based on clinically meaningful thresholds. This approach draws on existing analytical methods described in the receiver operating characteristic curve literature while presenting an extension for handling a continuous outcome. Application of this method to an independent test sample results in greater than 98% positive predictive value for CD4 count change. The prediction algorithm is derived based on a cohort of n = 270 HIV-1 infected individuals from the Royal Free Hospital, London who were followed for up to three years from initiation of ART. A test sample comprised of n = 72 individuals from Philadelphia and followed for a similar length of time is used for validation. Results suggest that this approach may be a useful tool for prioritizing limited laboratory resources for CD4 testing after subjects start antiretroviral therapy.