The following article is the sixth draft of the revised ASA Ethics Guidelines.  You are invited to read it and join the
discussion on it.
 

Post -Board-Meeting Draft for General Comments, December 22, 1998

 

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ETHICAL GUIDELINES FOR STATISTICAL PRACTICE

AMERICAN STATISTICAL ASSOCIATION

Committee on Professional Ethics

Executive Summary

This document contains two parts: I. Preamble and II. Ethical Guidelines. The Preamble addresses A. Purpose, B. Statistics and Society, and C. Shared Values. The purpose of the document is to encourage ethical and effective statistical work in morally conducive working environments. It is also intended to assist students in learning to perform statistical work responsibly. Statistics plays a vital role in many aspects of science, the economy, governance, and even entertainment. It is important that all those doing this work recognize their potential impact on the broader society. Because of this, they have basic ethical obligations to perform the work responsibly and, beyond that, they are also encouraged to exercise "good professional citizenship" directed at improving the public climate for, understanding of, and respect for the use of statistics throughout its range of applications.

The Ethical Guidelines address eight general topic areas and specify important ethical considerations under each topic. A. Professionalism points out the need for competence, judgment, diligence, self respect, and worthiness of the respect of other people. B. Responsibilities to Funders, Clients, and Employers addresses the care needed to assure that statistical work is suitable to the needs and the resources of those who are paying for it, that they understand the capabilities and limitations of the statistical contribution to solving their problem, and that their confidential information is protected. C. Responsibilities in Publications and Testimony addresses the need to report sufficient information to allow other practitioners a clear understanding of the intent of the work, how it was performed and by whom, and any limitations on its validity. D. Responsibilities to Research Subjects addresses requirements to protect the interests of human and animal subjects of research - not only during the collection of data, but also in the analysis, interpretation, and publication of resulting findings.

E. Responsibilities to Research Team Colleagues addresses the mutual responsibilities needed in multidisciplinary research teams. F. Responsibilities to Other Statisticians or Statistical Practitioners notes the interdependence of professionals doing similar work whether in the same or different organizations. Basically, they must contribute to the strength of their professions overall, by sharing nonproprietary data and methods, by participating in peer review, and by respecting differing professional opinions. G. Responsibilities Regarding Allegations of Misconduct addresses the sometimes painful process of investigating potential ethical violations and treating those involved with both justice and respect. Finally, we address H. Responsibilities of Organizations or Individuals Employing Statistical Practitioners, such as Employers, Attorneys, or other Clients. To gain the most value from statistical work, employers and clients need to understand that statistical ethics and statistical validity are highly interdependent. They must avoid any pressure to produce a particular apparent "result" regardless of its statistical validity. They must avoid the potential social harm that can result from disseminating false or misleading statistical work.

 I. PREAMBLE

 A. Purpose

The ASA Ethical Guidelines for Statistical Practice are intended to help statistical practitioners make and communicate ethical decisions. All professional users of statistical methods should urge clients, employers, researchers, policy makers, journalists, and the public to expect statistical practice to be in accordance with these guidelines and to object when that is not the case. While learning how to apply statistical theory to problems, students should be encouraged to follow these guidelines whether or not their target professional specialty will be "statistician." Employers, attorneys, and other clients of statistical practitioners have a responsibility to provide a moral environment that fosters use of the ethical guidelines.

B. Statistics and Society

The professional conduct of statistical analyses is essential to many aspects of society. The use of statistics in medical diagnoses and biomedical research may affect whether individuals live or die, whether their health is protected or jeopardized, and whether medical science advances or gets sidetracked. Life, death, and health, as well as efficiency, may be at stake in statistical analyses of transportation, occupational, or environmental safety. Early detection and control of new or recurrent infectious diseases depend on sound epidemiological statistics. Mental and social health may be at stake in psychological and sociological applications of statistical analysis.

Effective functioning of the economy depends on the availability of reliable, timely, and properly interpreted economic data. The profitability of individual firms depends in part on their quality control and their market research, both of which should rely on statistical methods. Agricultural productivity benefits greatly from statistically sound applications to research and to output reporting. Governmental policy decisions regarding public health, criminal justice, social equity, education, the environment, siting critical facilities, and other matters depend in part on sound statistics.

Scientific and engineering research in all disciplines requires careful design and analysis of experiments and observations. To the extent that uncertainty and measurement error are involved -- that is, in most research -- research design, data quality management, analysis, and interpretation are all crucially dependent on statistical concepts and methods. Even in theory, much of science and engineering inherently involves statistical variability. Variability, whether great or small, needs to be carefully examined both for random error and for possible researcher bias or wishful thinking.

C. Shared Values

Because of the dependence of society on sound statistical practice, all practitioners of statistics, whatever their training and occupation, have social obligations to perform their work in a professional, competent, and ethical manner. This document is directed to those whose primary occupation is statistics. Still, the principles expressed here should also guide the statistical work of professionals in all other disciplines that use statistical methods. All statistical practitioners are obliged to conduct their professional activities with responsible attention to:

1. The social value of one's work and the consequences of how well or poorly it is performed.

2. The need to avoid slanting statistical work toward predetermined outcomes. (It is acceptable to advocate a position; it is not acceptable to misapply statistical methods in doing so.)

3. Statistics as a science. (As in all science, understanding evolves. Statisticians have a body of established knowledge, but also many open issues that deserve frank discussion.)

4. Maintaining and upgrading competence in one's work.

5. Following applicable laws and regulations, but also seeking to change any ethically inappropriate laws or regulations.

In addition to ethical obligations, good professional citizenship encourages:

6. Collegiality and civility with fellow professionals.

7. Support for improved public understanding of and respect for statistics.

8. Support for sound statistical practice, especially when it is unfairly criticized.

9. Exposure of dishonest or incompetent uses of statistics.

10. Service to the profession as a statistical editor, reviewer, or association official.

11. Preservation of data archives.

II. ETHICAL GUIDELINES

 A. Professionalism

1. Strive for practical significance, not just statistical significance. Typically, combine competent understanding of the subject matter issues, statistical protocols that are clearly defined before looking at the data, and power analyses or similar justification of both the practical significance of the study and the sample sizes needed for valid results.

2. Use data selection processes that will be consistent with clear and unambiguous treatment of the issues during the research and with accurate understanding of that treatment by readers of the resulting publication(s). Consider possible researcher or data provider bias as well as random variation.

3. Maintain currency in dynamically evolving statistical methodology; yesterday's preferred methods may be barely acceptable today and totally obsolete tomorrow.

4. Assure that adequate statistical expertise and adequate subject matter expertise both are applied to any planned study. If this criterion is not met initially, it is important to add the missing expertise before completing the study design.

5. Use only statistical methodologies suitable to the data and to valid results.

6. Do not join a research project unless you can expect to achieve valid results and unless you feel assured that your name will not be in any way associated with the project or resulting publications without your explicit consent.

7. Recognize that automated statistical computation alone does not constitute adequate statistical analysis; it is also necessary to understand the theory, the data, and the methods used in each statistical study. This goal is served best when a competent statistical practitioner is included early in the research design, preferably in the planning stage.

8. Recognize that any statistical test has a random chance of indicating significance when it is not really present. Running multiple tests on the same data set at the same stage of an analysis increases the chance of obtaining at least one invalid result. Selecting the one "significant" result from a multiplicity of parallel tests poses a grave risk of an incorrect conclusion. Failure to disclose the full extent of tests and their results in such a case would be highly misleading.

9. Respect and acknowledge the contributions and the intellectual property of others.

10. Disclose conflicts of interest, financial and otherwise, and resolve them. This may sometimes require divestiture of the conflicting personal interest or recusal or withdrawal from the professional activity. Examples where conflict of interest may be problematic include grant reviews, other peer reviews, and tensions between scholarship and personal or family financial interests.

11. Provide only such expert testimony as you would be content to have peer reviewed.

B. Responsibilities to Funders, Clients, Employers

1. Where appropriate, present to a client or employer choices among valid alternative statistical approaches that may vary in scope, cost, or precision.

2. Clearly state one's statistical qualifications and experience relevant to one's work.

3. Clarify the respective roles of different participants in studies to be undertaken.

4. Explain any expected adverse consequences of failure to follow through on an agreed sampling or analytic plan.

5. Apply statistical sampling and analysis procedures objectively, without regard for outcome.

6. Statistical methods may be broadly applicable to many classes of problem or application. Statistical innovators may well be entitled to monetary or other rewards for their writings, software, or research results. This should not preclude their making new statistical knowledge widely available, at affordable prices where pricing is appropriate, so as to allow benefits to society at large beyond their own scope of applications.

7. Guard privileged information of the employer, client, or funder.

8. Fulfill all commitments.

9. Accept full responsibility for one's professional performance.

C. Responsibilities in Publications and Testimony

1. Maintain personal responsibility for all work bearing one's name; avoid undertaking

work or coauthoring publications for which one would not want to acknowledge responsibility. Conversely, accept (or insist upon) appropriate authorship or acknowledgment for professional statistical contributions to research and the resulting publications or testimony.

2. Report statistical and substantive assumptions made in the study.

3. In publications or testimony, identify who is responsible for the statistical work if it would not otherwise be apparent.

4. Preferably, authorship order in statistical publications should be by degree of intellectual contribution to the study and to the material to be published, to the extent that such ordering can feasibly be determined. When some other rule of authorship order is used in a statistical publication, the rule used should be disclosed in a footnote or endnote. (Where authorship order by contribution is assumed by those making decisions about hiring, promotion, or tenure, for example, failure to disclose an alternative rule may improperly damage or advance careers.)

5. Account for all data considered in a study and explain the sample(s) actually used.

6. Report the sources and assessed adequacy of the data.

7. Report the data cleaning and screening procedures used, including any imputation.

8. Clearly and fully report the statistical methods used and their relation to the assumptions so as to support statistical peer review.

9. In publications or testimony, identify the ultimate paying sponsor of the study, the stated purpose, and the intended use of the study results.

10. When reporting analyses of volunteer data or other data not representative of a defined population, include appropriate disclaimers.

11. Report the limits of statistical inference of the study and possible sources of error, both random and systematic. For example, disclose any significant failure to follow through fully on an agreed sampling or analytic plan, and explain any resulting adverse consequences.

12. Share (non-proprietary) data used in published studies to aid peer review and replication.

13. As appropriate, promptly and publicly correct any errors discovered after publication.

14. Write with consideration of the intended audience. (For the general public, convey the scope, relevance, and conclusions of a study without technical distractions. For the professional literature, strive to answer the questions likely to occur to your peers.)

D. Responsibilities to Research Subjects, including survey respondents and persons and organizations involved with administrative records, as well as subjects of physically or psychologically invasive research.

1. Know and adhere to appropriate rules for protection of human subjects, including protection of special populations who may not be fully able to protect their own interests. Assure adequate planning to support the practical value of the research, the validity of expected results, and consideration of all ethical issues involved. [U. S. federal guidelines are administered by the Office for Protection from Research Risks (OPRR) at the National Institutes of Health (NIH), supplemented as appropriate by other federal Departments and agencies. The regulations are defined in Title 45 of the Code of Federal Regulations, Chapter 46 (45CFR46). State and local rules, private organization guidelines, and laws, regulations or guidelines in other countries may differ.]

2. Avoid use of excessive or inadequate numbers of research subjects by making informed recommendations for study size. These may be based on prospective power analysis or the planned precision of the study endpoint(s), also considering the feasibility of obtaining research subjects and the value of the data elements to be collected.

3. Avoid excessive risk to research subjects and excessive imposition on their time and privacy.

4. Protect the privacy and confidentiality of research subjects and data concerning them whether obtained directly from the subjects, from other persons, or from administrative records. Anticipate secondary and indirect uses of the data when obtaining approvals from research subjects. Generally, make provision at least for a later independent replication of an analysis by an outside party.

5. Be aware of legal limitations on privacy and confidentiality assurances. Do not, for example, imply protection of privacy and confidentiality from legal processes of discovery unless explicitly authorized to do so.

6. Prior to participating in a study involving human beings or organizations, analyzing data from such a study, or accepting resulting manuscripts for review, consider whether appropriate research subject approvals were obtained. (This will lower your risk of learning only after the fact that you had collaborated on an unethical study.) Consider also what assurances of privacy and confidentiality were given and abide by those assurances.

7. Avoid or minimize the use of deception. Where it is necessary and provides significant knowledge, as in some psychological, sociological, and other research, assure prior independent ethical review of the protocol and continued monitoring of the research.

8. Where full disclosure of study parameters to subjects or to other investigators is not advisable, as in some randomized clinical trials, at least inform them of the nature of the information withheld and the purpose of withholding it.

9. Know and adhere to appropriate animal welfare guidelines in research involving animals. Assure that competent understanding of the subject matter combines with power analysis or similar justification to support the practical value of the research and the sample sizes to be used.

E. Responsibilities to Research Team Colleagues

1. Inform colleagues of other disciplines about relevant aspects of statistical ethics.

2. Promote effective and efficient use of statistics by the research team.

3. Respect the ethical obligations of members of other disciplines as well as one's own.

4. Assure professional quality reporting of the statistical design and analysis.

5. Avoid compromising statistical validity for expediency.

F. Responsibilities to Other Statisticians or Statistical Practitioners 

1. Promote sharing of (nonproprietary) data and methods. As appropriate, make suitably documented data available for replicate analyses, metadata studies, and other suitable research by qualified investigators.

2. Be willing to help strengthen the work of others through appropriate peer review. When doing so, complete the review promptly and well.

3. Assess methods, not individuals.

4. Respect differences of opinion.

5. Make decisions regarding statistical practitioners' hiring, firing, promotion, work assignments, publications and presentations, candidacy for offices and awards, funding or approval of research, and other professional matters on the basis of the professional qualifications and contributions of the individual. Avoid harassment of or discrimination against statistical practitioners on professionally irrelevant bases such as: race, color, ethnicity, sex, sexual orientation, national origin, age, religion, nationality, or any disability.

G. Responsibilities Regarding Allegations of Misconduct:

1. Avoid condoning or appearing to condone careless, incompetent, or unethical conduct of

statistical studies in one's working environment or elsewhere.

2. It is not sufficient to deplore only plagiarism and data fabrication or falsification. Misconduct more broadly includes all professional dishonesty, by commission or omission, and, within the realm of professional activities and expression, all harmful disrespect for people, unauthorized taking of their intellectual and physical property, and unjustified detraction from their reputations.

3. Recognize that differences of opinion and honest error do not constitute misconduct; they warrant discussion but not accusation. Questionable scientific practices may or may not constitute misconduct, depending on their nature and the definition of misconduct used.

4. If involved in a misconduct investigation, know and follow prescribed procedures. Maintain confidentiality during an investigation, but disclose the results honestly after the investigation has been completed.

5. Following a misconduct investigation, support appropriate efforts of the accused, the witnesses, and those reporting the possible scientific error or misconduct to resume their careers in as normal a manner as possible.

6. Do not condone retaliation against, or damaging the employability of, those who responsibly call attention to possible scientific error or misconduct.

H. Responsibilities of Organizations or Individuals Employing Statistical Practitioners, such as Employers, Attorneys, or other Clients.

1. Recognize that results of valid statistical studies cannot be guaranteed to conform to what those commissioning the study, or the statistical practitioner(s), may have expected or desired. Any measures taken to assure a particular outcome will lessen the validity of the analysis.

2. Valid results can only result from competent work in a moral environment. Pressure on a statistical practitioner to deviate from the Guidelines above is likely to damage both the validity of study results and the professional credibility of the practitioner.

3. Those who have funded the development of new statistical innovations are entitled to monetary and other rewards for their resulting products, software, or research results. Certainly their own data and trade secrets are proprietary. This should not preclude their making new statistical knowledge widely available, at affordable prices where pricing is appropriate, so as to allow benefits to society at large beyond their own scope of applications.

4. Statistical practitioners and others have a social responsibility to support sound statistical analysis and to expose incompetent or corrupt statistical practice. In cases of conflict, statistical practitioners and those employing them are encouraged to resolve issues of ethical practice privately if possible. If private resolution is not possible, recognize that statistical practitioners have an ethical obligation to expose incompetent or corrupt practice before it can cause avoidable harm to research subjects or to society at large.

5. Within organizations and within professions using statistical methods generally, statistical practitioners who have greater prestige, power, or status have a responsibility to protect the professional freedom and responsibility of more subordinate statistical practitioners to comply with these Guidelines.

6. Statistical practitioners should not be included in authorship or in acknowledgment regarding projects or publications without their explicit permission.

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American Statistical Association Committee on Professional Ethics members (1998): John C. Bailar, Paula H. Diehr, Susan S. Ellenberg, John S. Gardenier (Chair), Lilliam Kingsbury, David M. Levy, Richard F. Potthoff, Jerome Sacks, Chamont W. Wang.

Other contributing advisors in the preparation of these guidelines: Mark Frankel (American Association for the Advancement of Science), Mary Grace Kovar, Lisa McShane, Michael O'Fallon, Juliet Shaffer, and Fritz Scheuren.

Thanks to the many persons who commented on successive drafts or participated in discussions of the Guidelines at the 1998 Joint Statistical Meetings, Dallas, Texas.

ASA Executive Director, Ray A. Waller; ASA Staff Liaison, Derek Lawlor

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