Professional development of statisticians in the pharmaceutical sector: evolution over the past decade and into the future

The adoption of The International Conference on Harmonization Tripartite Guideline: Statistical Principles for Clinical Trials (ICH-E9) has provided a foundation for the application of statistical principles in clinical research and raised awareness of the value of a statistical contribution to the wider pharmaceutical R&D process. In addition, over the past decade globalization of the pharmaceutical R&D process and the measures taken to address reduced productivity and spiralling costs have impacted on the roles and career opportunities for statisticians working in the pharmaceutical sector. This has enhanced the need for continuing professional development to equip statisticians with the skills to fully contribute to creating innovative solutions. In the future, key areas of focus are the establishment of professional standards for statistical work and increasing the collaboration between statisticians working in industry, regulatory agencies and academia. In addition, the diversity of roles and potential career paths for statisticians embarking on a career in the pharmaceutical sector emphasizes the importance of mentoring and coaching. For the more experienced statisticians, there are unprecedented opportunities to lead and innovate.     

Providing Consulting Experiences Through Role Playing in a Graduate Statistics Course

An effective method for improving the communication skills of graduate students in statistics and biostatistics is to provide consultations with non‐statistical researchers. Unfortunately, those experiences can be difficult to arrange or occur too infrequently to be reliable. The current study sought to help students develop both written and oral communication skills within an existing graduate biostatistics course by having students partake in role‐playing consultations. Though the class size was small, the students felt these activities helped improve their oral and written communication skills, and made them more aware of a biostatistician's role in consulting. There was also modest improvement in the students perceived function as a consulting biostatistician. Simulated consultations can be an effective educational tool for promoting the development of soft skills necessary for developing successful statisticians, can be implemented in existing courses, and do not require reliance upon external collaborators. Embedding these types of exercises within an existing curriculum can also be a cost‐effective alternative for programs that do not have formal consulting training.     

Strategies for Success: Early-Stage Collaborating Biostatistics Faculty in an Academic Health Center

Collaborative biostatistics faculty (CBF) are increasingly valued by academic health centers (AHCs) for their role in increasing success rates of grants and publications, and educating medical students and clinical researchers. Some AHCs have a biostatistics department that consists of only biostatisticians focused on methodological research, collaborative research, and education. Others may have a biostatistics unit within an interdisciplinary department, or statisticians recruited into clinical departments. Within each model, there is also variability in environment, influenced by the chair's background, research focus of colleagues, type of students taught, funding sources, and whether the department is in a medical school or school of public health. CBF appointments may be tenure track or nontenure, and expectations for promotion may vary greatly depending on the type of department, track, and the AHC. In this article, the authors identify strategies for developing early-stage CBFs in four domains: (1) Influence of department/environment, (2) Skills to develop, (3) Ways to increase productivity, and (4) Ways to document accomplishments. Graduating students and postdoctoral fellows should consider the first domain when choosing a faculty position. Early-stage CBFs will benefit by understanding the requirements of their environment early in their appointment and by modifying the provided progression grid with their chair and mentoring team as needed. Following this personalized grid will increase the chances of a satisfying career with appropriate recognition for academic accomplishments.     

Re-Defining the Who,When, and Where of Mentoring for Professional Statisticians

Organizations tailor their mentoring strategies to accommodate internal resources and preferences, producing different approaches in academic, government, and corporate environments. Across these settings, three common barriers impede effective mentoring of statisticians: overspecialization, time constraints, and geographic dispersion. The authors share mentoring strategies that have emerged at their organization, Mathematica Policy Research, to overcome these obstacles. Practices include creating a methodology working group to unite researchers with diverse backgrounds, integrating mentoring into existing workflows, and harnessing modern technological infrastructure to facilitate virtual mentoring. Although these strategies emerged within a specific professional context, they suggest opportunities for statisticians to expand the channels through which mentorship can occur.     

The Big Tent for Statistics: Mentoring Required

Research supports the positive impact of mentoring on both job and career satisfaction. Recognizing this, the American Statistical Association (ASA) has started a new mission-centered focus on mentoring. This article describes the development and implementation of meeting-based mentoring programs at four ASA conferences in 2014 and 2015. We present results of the feedback evaluations from program participants and use them to motivate recommendations for creating and running conference mentoring programs and overcoming common challenges. These recommendations are applicable to creating and running conference mentoring programs in any field. We conclude with a discussion of the opportunities for the ASA to augment its mentoring programs in support of the professional development of its members.     

统计学专业改造的方向

经济学体制改革以来,我国为数不少的企业和机关撤并统计结构,削减统计人员,基层统计工作遭到较严重的削弱。此种现实引发了统计教育的震荡：高等院校统计专业不同程度地出现了“招生难、毕业分配难”的局面,致使有的高校撤并了统计专业,有的削减了招生规模,有的改为隔年招生,还有的学校正在酝酿着撤消统计专业,改上其他专业。无独有偶,遥远的太平洋彼岸也有类似情况发生。据美国统计学者Ronald?L?Iman 透露：1970年至1990年,美国统计学博士生的年平均增长率仅为0.24%。目前一些大学统计系已被撤销,有些正面临被关闭的危险。Ronald?L?Iman认为：“这种局面的形成,并非大学自身所愿,而是由一些主要工业行业统计机构的撤销与大大削弱的冲击所致。”据国家教委负责人透露:我国将于明年实行招生“并轨”,而且“招生并轨之日,就是毕业生自主择业之时”。到那时,国家不包分配了,还能有多少考生报统计学专业？有多少考生愿意“服从分配”调到统计学专业呢？统计学专业何去何从——人们不禁为之忧心忡忡。     

Leadership in Statistics: Increasing Our Value and Visibility

Scientists in every discipline are generating data more rapidly than ever before, resulting in an increasing need for statistical skills at a time when there is decreasing visibility for the field of statistics. Resolving this paradox requires stronger statistical leadership to guide multidisciplinary teams in the design and planning of scientific research and making decisions based on data. It requires more effective communication to nonstatisticians of the value of statistics in using data to answer questions, predict outcomes, and support decision-making in the face of uncertainty. It also requires a greater appreciation of the unique capabilities of alternative quantitative disciplines such as machine learning, data science, pharmacometrics, and bioinformatics which represent an opportunity for statisticians to achieve greater impact through collaborative partnership. Examples taken from pharmaceutical drug development are used to illustrate the concept of statistical leadership in a collaborative multidisciplinary team environment.     

An Eight-Step Guide to Creating and Sustaining a Mentoring Program

Mentoring is an extremely valuable activity for both individuals and organizations. Mentoring within organizations can develop and integrate employees into their corporate culture. Mentoring outside the mentees’ work groups or through professional development organizations can give broader perspective and support, especially in times of transition. But mentoring programs require tremendous effort to start, organize, and maintain. Few last more than two years. This article provides a structured approach to starting and sustaining a successful program. The steps include understanding an organization’s particular needs, learning from small pilot programs, following up with mentoring pairs during a committed formal mentoring period, and evaluating results from each program’s cycle to learn and grow the program. Supplementary materials for this article are available online.     

Teaching Communication in a Statistical Collaboration Course: A Feasible,Project-Based,Multimodal Curriculum

Many schools offer a statistical collaboration curriculum using standard instructional methods such as lectures whereby students are taught to successfully apply their training. The process of building statisticians' collaborative skills and characteristics can be challenging due to logistical issues, time constraints, unstructured research problems, and resources. Instructors vary in their pedagogy and topics taught, and students' experiences vary. There is a dearth of literature describing how to implement a course integrating communication skills, critical thinking, collaboration, and the integration of team members in a learner-centered format. Few courses integrate behavior-based learning using role-playing, video demonstration and feedback, case-based teaching activities, and presentation of basic statistical concepts. We have developed and implemented a two-semester biostatistics collaboration course, of which the purpose is to develop the students' knowledge, skills, attitudes, and behaviors necessary to interact effectively with investigators. Our innovative curriculum uses a multimodal, project-based, experiential process to address real-world problems provided by real and/or simulated collaborators while minimizing usual challenges. Rubrics and peer evaluation forms are offered as online supplementary materials. This article describes how a collaboration curriculum focusing on communication and team practice is feasible, how it enhances skill and professionalism, and how it can be implemented at other institutions.     

大数据时代的统计教育

2014年11月,美国统计学会适应大数据时代的要求,发布了统计学本科专业指导性教学纲要。而在2013年,我国统计类本科专业刚刚进行了一次较大调整,目前的专业课程设置和教学内容改革还处于探索阶段。美国统计学会发布的这份指导性教学纲要对于推进我国统计类本科专业教育改革具有重要借鉴意义。本文首先概括性地介绍了美国统计学会发布的统计学本科专业指导性教学纲要的核心内容,包括统计专业本科生应该掌握的基本技能和应该修读的主要课程,然后分析了我国统计类本科专业教育存在的问题,并提出了在大数据时代改进我国统计类本科专业教育的几点建议。     

Meeting Student Needs for Multivariate Data Analysis: A Case Study in Teaching an Undergraduate Multivariate Data Analysis Course

Modern students encounter large, messy datasets long before setting foot in our classrooms. Many of these students need to develop skills in exploratory data analysis and multivariate analysis techniques for their jobs after college, but such topics are not covered in traditional introductory statistics courses. This case study describes my experience in designing and teaching an undergraduate course on multivariate data analysis with minimal prerequisites, using real data, active learning, and other interactive activities to help students tackle the material. Multivariate topics covered include clustering and classification (among others) for exploratory data analysis and an introduction to algorithmic modeling. Supplementary materials for this article are available online.     

Preparing Statisticians for Careers in Industry: Report of the ASA Section on Statistical Education Committee on Training of Statisticians for Industry

This report provides guidelines for universities to consider in developing programs for training statisticians who will work in industry. Useful information for students who are considering industrial employment is also included. The recommended programs focus on real problems and the statistical theory and methodology that are useful in their solution. Technical competence is only one of many factors that industry considers when hiring and promoting statisticians. When a statistician leaves school, his or her skills and experiences should include statistical knowledge, practical problem solving, consulting practice, and the ability to communicate orally and in writing with nonstatisticians. There are many details that must be worked out (e.g., content of specific courses and organization of consulting internship programs), and it is hoped that the statistical societies and universities will form committees, hold conferences, and develop programs to address these issues further. Many of our recommendations apply more broadly to the training of all types of practicing statisticians.     

Developing a Career in the Practice of Statistics: The Mentor's Perspective

The W.J. Dixon Award for Excellence in Statistical Consulting is given by the American Statistical Association to “a distinguished individual who has demonstrated excellence in statistical consulting or developed and contributed new methods, software, or ways of thinking that improve statistical practice in general.” In this article, five of the seven past recipients of this career-capping award share their experiences and perspectives through 10 stepping stones that move a practicing statistician from consultant to collaborator to leader. We highlight the need for mentorship throughout the discussion, and provide direction for statisticians who would like to incorporate this advice into their careers.     

A New Direction for Library Technical Services: Using Metadata Skills to Improve User Accessibility

Abstract

An increased awareness about the importance of resource accessibility for all library users has set the stage for transforming traditional cataloger roles into a new realm of possibility. The Acquisitions & Discovery (A&D) and the User Experience (UX) departments of North Carolina State University Libraries have formed a partnership to explore the benefits of working together amidst this climate of innovation and change. A pilot project was created to develop a workflow through which technical services staff can use their metadata skills to help resolve accessibility issues found on the Libraries’ main website. By performing this work, staff can grow in technical expertise, enhance the quality of metadata in web content, and build mutually beneficial partnerships within the library community.     

Enhancing statistical education by using role-plays of consultations

Summary.  Role-plays in which students act as clients and statistical consultants to each other in pairs have proved to be an effective class exercise. As well as helping to teach statistical methodology, they are effective at encouraging statistical thinking, problem solving, the use of context in applied statistical problems and improving attitudes towards statistics and the statistics profession. Furthermore, they are fun. This paper explores the advantages of using role-plays and provides some empirical evidence supporting their success. The paper argues that there is a place for teaching statistical consulting skills well before the traditional post-graduate qualification in statistics, including to school students with no knowledge of techniques in statistical inference.     

大学生数学成绩影响因素的实证分析

伴随着近几年高校的扩大招生,部分大学生的数学成绩显著下降。用统计学软件SPSS 13.0对哈尔滨工程大学部分学生的高等数学成绩及其相关因素进行统计分析,考察学生的高考数学成绩、性别、生源所在地等因素对其大学数学成绩的影响。在给出了一些切实可行的对策和建议的同时,指出培养大学生学习的主动性和研究探索精神,已经成为当今高校教师和教育工作者培养高素质人才和提高教学水平的关键。     

Multidimensional Scaling for Selecting Small Groups in College Courses

Many college courses use group work as a part of the learning and evaluation process. Class groups are often selected randomly or by allowing students to organize groups themselves. However, if it is desired to control some aspect of the group structure, such as increasing schedule compatibility within groups, multidimensional scaling can be used to form such groups. This article describes how this has been adopted in an undergraduate statistics course. Resulting groups have been more homogeneous with respect to student schedules than groups selected randomly—an example from winter quarter 2004 increased correlations between student schedules from a mean of .29 before grouping to a within-group mean of .50. Further, the exercise allows opportunities to discuss a wealth of statistical concepts in class, including surveys, association measures, multidimensional scaling, and statistical graphics.     

Teaching Statistical Consulting Before Statistical Methodology

This paper outlines and discusses the advantages of an ‘Introduction to Statistical Consulting’ course (ISC) that exposes students to statistical consulting early in their studies. The course is intended for students before, or while, they study their units in statistical techniques, and assumes only a first‐year introductory statistics unit. The course exposes undergraduate students to the application of statistics and helps develop statistical thinking. An important goal is to introduce students to work as a statistician early in their studies because this motivates some students to study statistics further and provides a framework to motivate the learning of further statistical techniques. The ISC has proved popular with students, and this paper discusses the reasons for this popularity and the benefits of an ISC to statistical education and the statistics profession.     

Dealing with the biased effects issue when handling huge datasets: the case of INVALSI data

The increasing prevalence of huge datasets addresses the research to appropriate statistical methods for solving troubles caused by their complexity. On the one hand, several techniques are mentioned in the literature, especially for the time-consuming and variables reduction issues. On the other, less debate is devoted to the statistical inference issue. Indeed, a large number of involved statistical units may lead to wrongly consider as significant variables without any actual impact on the phenomenon under study. This paper suggests a suitable subsampling procedure for the reduction of the number of statistical units and provides a novel index for the assessment of the significance effects. The proposal is validated by comparing results obtained from the analysis on the original data to those obtained from the proposed subsampling approach. The illustrative application focuses on the educational dataset made available by the National Committee for the Evaluation of the Italian Education Systems (INVALSI). This dataset collects information about the student features and achievements in Maths within the lower secondary schools of the Lombardy region (Italy). Due to the hierarchical structure of the data, a multilevel model is implemented with the purpose of investigating the effects of both individual and school factors on student Maths score.