1 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 becomes sidetracked. Life, death, and health may be at stake in statistical analyses of occupational, environmental, or transportation 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 market research, both of which should rely on statistical methods. Agricultural productivity benefits greatly from statistically sound applications to research and output reporting. Governmental policy decisions regarding public health, criminal justice, social equity, education, the environment, national defense, and security depend in part on sound statistics.
2 Misconduct is not limited to instances of plagiarism and data fabrication or falsification. More broadly, misconduct includes all professional dishonesty, by commission or omission, and, within the realm of professional activities and expression, all harmful disrespect for people, unauthorized use of their intellectual and physical property, and unjustified detraction from their reputations.
3 Typically, each study should be based on a competent understanding of the subject-matter issues and statistical protocols that are clearly defined for the stage (exploratory, intermediate, or final) of analysis before looking at those data that will be decisive for that stage and technical criteria to justify both the practical relevance of the study and the amount of data to be used.
4 Running multiple tests on the same data set at the same stage of an analysis increases the chance of obtaining at least one in- valid 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.
5 For example, address the multiple potentially confounding factors in observational studies and use due caution in drawing causal inferences. The fact that a procedure is automated does not ensure its correctness or appropriateness; it is also necessary to understand the theory, data, and methods used in each statistical study.
6 Preferably, authorship order in statistical publications should be by degree of intellectual contribution to the study and 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 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.
7 This may sometimes require divestiture of the conflicting personal interest 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.
8 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.
9 For example, disclose any significant failure to follow through fully on an agreed sampling or analytic plan and explain any resulting adverse consequences. Address the suitability of the analytic methods and their inherent assumptions relative to the circumstances of the specific study. Identify the computer routines used to implement the analytic methods.
10 Statisticians are encouraged to participate in professional activities contributing to the improvement of the community and to work that elevates the statistical profession in the United States and the world. It is recognized that the ability to do pro bono work may be limited by the conditions of the statistician’s employment and personal situations, but statisticians should be open to opportunities for pro bono and other work, including service to the local community or to international organizations. Service to the profession—including service on ASA committees, sections, and chapters—is also encouraged.
11 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.
12 Ensure adequate planning to support the practical value of the research, validity of expected results, ability to provide the protection promised, and consideration of all other ethical issues involved.
13 These recommendations may be based on prospective power analysis, the planned precision of the study end- point(s), or other methods to ensure appropriate scope to either frequentist or Bayesian approaches. Study scope also should take into consideration the feasibility of obtaining research subjects and the value of the data elements to be collected.
14 Appropriate approval is not necessarily given by the research subjects themselves. Approval may be required from a parent or legal guardian who must consent, and the actual participant may be required to assent in some cases. This includes legal guardians for minors and adults who are unable to give consent. In animal studies, statisticians should enquire as to proper forms of owner or institutional consent for animals that are part of a research project.
In all cases, avoid or minimize the use of deception. Where it is necessary and provides significant knowledge—as in some psychological, sociological, and other research—ensure prior independent ethical review of the protocol and continued monitoring of the research. Where full disclosure of study parameters to subjects or other investigators is not advisable, as in some randomized clinical trials, generally inform them of the nature of the information withheld and the reason for withholding it. As with deception, ensure independent ethical review of the protocol and continued monitoring of the research.
15 All research is constrained by resources, including the available funding, timing, and personnel. Thus few, if any, studies can achieve the highest standards imaginable. However, the statistician should always strive to achieve the most valid results with the resources available and avoid working on studies likely to produce misleading or meaningless results.
16 This safeguard will lower your risk of learning only after the fact that you have collaborated on an unethical study.
17 In cases of conflict, statistical practitioners and those employing them are encouraged to resolve issues of ethical practice privately. If private resolution is not possible, recognize that statistical practitioners have an ethical obligation to expose incompetent or corrupt practice before it can cause harm to research subjects or society at large.
18 Any measures taken to ensure a particular outcome will lessen the validity of the analysis. Pressure on a statistical practitioner to deviate from these guidelines is likely to damage both the validity of study results and the professional credibility of the practitioner.
19 Within organizations and within professions using statistical methods generally, statistics practitioners with greater prestige, power, or status have a responsibility to protect the professional freedom and responsibility of more subordinate statistical practitioners who comply with these guidelines.