Ethical Use of Statistics in Research

1. Ethical Use of Statistics in Research Dr. Larry A. Nelson, Professor Emeritus of Statistics and Assistant Dean for International Programs, College of Agriculture and Life Sciences

2. Background • Recent Interest • Development of a course on Research Ethics - 1 hour credit - To be required at some cooperating institutions - One component – Ethical Use of Statistics - Discuss Proposed content of the module today - Value your ideas and comment • Importance of Statistics in Research Credit to Michael Crotty. Marcia Gumpertz – moral support and guidance for several years

3. Ethics in Application of Statistics • Teaching, consulting for planning, execution, data analysis and interpretation • Overheard on NCSU Campus History Professor: “Be suspicious of a professional who attempts to develop a set of ethics for his or her own field” • Undergraduate Student in Philosophy, “I hate Ethics”

4. Population, Process, Data Relationship • Relationships • Poor Practice – Making a Mistake or Misconduct: Importance of competence and Maturity in Research and use of Statistics • Objectivity and Trustworthiness • Objectivity in Asking Right Questions • Objectivity in Answering the Questions

5. Responsibility of the Researcher and Statistician PLANNING PHASE

6. EXECUTION PHASE

7. ANALYSIS PHASE

8. INTERPRETATION AND REPORTING

9. RESPONSIBILITY OF RESEARCHER AND STATISTICIAN • Promote high standards of scientific inquiry and professionalism • Involve appropriate techniques for research • Honor the rights of other researchers – give credit to other researcher where due • Consider interdependence of natural, social and technological systems • Give objectivity a major role • Guard against misinterpretation and misuse of data

10. Good Practices Checklist • Planning is very important in experimentation • Statistician can assist in planning • Planning does not ensure success but avoids built-in disasters • Statistics cannot compensate for negative impacts of persisting in a faulty line of research

11. Good Planning Can Prevent: • Costly waste of resources • Difficult statistical analysis • Data for which interpretation is controversial • An experiment which is precise but which answers the wrong questions

12. Setting Up Original Hypothesis Objectively 2 Rules: 1. Hypothesis should be clearly related to original problem 2. The hypothesis should be stated as simply as possible

13. IV. Discipline Specific Ethical Issues Flexibility needed: Ethics vary Among Different Application Areas Business Application: Withholding Negative Results Problem Formulation Important – Involve Statistician Design Considerations: Costs, Definition of Population, Sampling Frame

14. Statistician provides report but does not make decisions for management Company should have same responsibilities to a salaried statistician as to a consulting one (and conversely). See: Deming, W.W., Sample Designs in Business Research. Wiley NY 1960.

15. Medical Application • Medical review boards • Informed consent • Methods of selecting subjects • Withholding a treatment to a control group • Access to data • Confidentiality of identity of subjects

16. V. Ethical Issues in Interpretation and Reporting • Insufficient statistical methods description • Statistical significance vs. practical significance • Access to data • Kinds of means in the factorial experiment reporting • Reporting of measures of dispersion • Proper decimal reporting • Bonafide scientific conclusions vs. speculation • Clarity of reporting • Indication that results are not final word • Enumeration of new study questions

17. VI. Case Studies • Skagerrak Case – Precautionary Principle 2 Highly respected scientists interpret their results differently Case emphasized 2 critical aspects of research • The actual statistical analysis • How and when to disseminate the information from research • Elton’s Withholding of Anomalous Data • US Census: Use of sample survey methods to adjust census counts

18. References Cited and Some Reading Material on Ethical Use of Statistics: Bailan, John C 1997 Science, Statistics and Deception” in Research Ethics: A Reader, (Deni Elliott and Judy E. Stein, eds. University Press of New England, Honover). Buhl-Mortensen and Stellan Welin 1998 The Ethics of Doing Policy Relevant Science: The Precautionary Principle and the Significance of Non-Significant Results, Science and Engineering Ethics, Opragen Publications, Surrey. Deming, W.E. 1960 Sample Designs in Business Research, John Wiley and Sons, New York. Cooper, B. Holmes 1990 The Honest Truth About Lying with Statistics, Charles C. Thomas, Springfield. Huff, Darrel 1954 How to Lie with Statistics, W.W. Norton & Co. New York. Leavitt, Fred 2001 Evaluating Scientific Research: Separating Fact from Fiction, Prentice Hall, Upper Saddle River.

19. Moore, David S. 2006 Data Ethics, An Introduction, From the Supplemental Material for David S. Moore and George P. McCabe: Introduction to the Practice of Statistics, 5th Ed. W.H. Freeman. Pittinger, David, Hypothesis Testing as a Moral Choice, in Ethics and Behavior (II (2), 2001). Whitbeck, Caroline 1998 Responsibility of research Integrity, Chapter 6 in Ethics in Engineering Practice and Research. Cambridge University Press, Cambridge. Professional Codes of Ethics for Statistics: Web Sites American Statistical Association: http://www.amstat.org/profession/index.cfm?fuseaction=ethicalstatistics International Statistical Institute: http://isi.cbs.nl/ethics.htm