ISI Declaration on Professional Ethics
The likely consequences of collecting and disseminating various types of data should be considered and explored, and efforts made to guard against predictable misinterpretation or misuse. Findings should be communicated for the benefit of the widest possible community.
Statistical inquiry is predicated on the belief that greater access to well-grounded information is beneficial to society. The fact that statistical information can be misconstrued or misused, or that its impact can be different on different groups, is not in itself a convincing argument against its collection and dissemination. Nonetheless, the statistician should consider the likely consequences of collecting and disseminating various types of data and should guard against predictable misinterpretations or misuse.
All information, whether systematically collected or not, is subject to misuse. And no information is devoid of possible harm to one interest or another. Individuals may be harmed by their participation in statistical inquiries, or group interests may be damaged by certain findings. A particular district may, for instance, be negatively stereotyped by a statistical inquiry which finds that it contains a very high incidence of crime. A group interest may also be harmed by social or political action based on statistical findings. For instance, heavier policing of a district in which crime is found to be high may be introduced at the expense of lighter policing of a district in which crime is found to be high may be introduced at the expense of lighter policing in low crime districts. Such a move may be of aggregate benefit to society but to the detriment of some districts. Statisticians are not, however, in a position to prevent action based on statistical data. Indeed, to guard against the use of their findings would be to disparage the very purpose of much statistical inquiry. However, statisticians should act to the extent possible to inform the public if findings are misused or mislead.
Statisticians should uphold their professional integrity without fear or favor, only selecting and using methods designed to produce the most accurate results, consistent with accepted international practices,, presenting the findings openly, completely, and in a transparent manner. While statisticians operate within the value systems of their societies, they should not engage or collude in selecting methods designed to produce misleading results, or in misrepresenting statistical finds by commission or omission.
The pursuit of objectivity is a goal of science, though in practice it may be difficult to achieve at all times. Statistics is no exception. The selection of topics for attention may reflect a systematic bias in favour of certain cultural or personal values, In addition, the employment base of the statistician, the source of funding, and a range of other factors may impose certain priorities, obligations, and prohibitions. Even so, the statistician is never free of a responsibility to pursue objectivity and to be open about known barriers to its achievement. In particular, statisticians are bound by a professional obligations to resist approaches to data collection, processing, analysis, interpretation, and publication that are likely (explicitly or implicitly) to misinform or to mislead, rather than to advance knowledge.
3. Clarifying obligations and roles
The respective obligations of employer, client, or funder, and statistician in regard to the roles and responsibility of each should be spelled out and fully understood in advance. In providing advice or guidance, statisticians should take care to stay within their area of competence, and seek advice, as appropriate, from others with the relevant expertise.
4. Assessing alternatives impartially
Available methods and procedures for addressing a proposed inquiry should be considered and an impartial assessment provided the employer, client, or funder of the respective merits and limitations of alternatives, along with the proposed method.
Statisticians develop and use concepts and techniques for the collection, analysis or interpretation of data. Although they are not always in a position to determine the scope of their work or the way in which their data are used and disseminated, they are frequently able to influence these matters. In addition, they are in a position to devise more efficient uses of resources through, for example, developing sampling techniques or introducing new uses for existing data.
Academic statisticians may enjoy the greatest degree of autonomy over the scope of their work and the dissemination of their results. Even so, they are generally dependent on the decisions of funders, on the one hand, and journal editors, on the other, for the direction and publication of their inquiries.
Statisticians employed in the public sector and those employed in commerce and industry tend to have even less autonomy over that they do or how their data are utilised. Rules of secrecy may apply; pressure may be exerted to withhold or delay the publication of findings (or of certain findings); statistical series may be introduced or discontinued for reasons that have little to do with technical considerations. In these cases the final authority for decisions about an inquiry may rest with the employer or client.
Statisticians are most likely to avoid restrictions being placed on their work when they are able to stipulate in advance the issues over which they should maintain control. Government statisticians may, for example, gain agreement to announce dates of publication for various statistical series, thus creating an obligation to publish the data on the due dates regardless of intervening political factors. Similarly, statisticians in commercial contracts may specify that control over at least some of the findings (or details of methods) will rest in their hands rather than with their clients. The greatest problems seem to occur when such issues remain unresolved until the data emerge.
5. Avoiding Preempted Outcomes
Any attempt from employer, client, or any source to establish a predetermined outcome from a proposed statistical inquiry should be rejected, as should contractual conditions contingent upon such a requirement.
6. Guarding Privileged Information
Statisticians are frequently furnished with information by the employer, client, or funder who may legitimately require it to be kept confidential. Statistical methods and procedures that have been utilized to produce published data should not, however, be kept confidential.
The independent statistician or consultant appears to enjoy greater latitude than the employee-statistician to insist on the application of certain professional principles. In the case of the independent statistician, each relationship with a funder may be subject to a specific contract in which roles and obligations may be specified in advance, suggesting some greater latitude. In the employee's case, by contrast, his or her contract is not project-specific and generally comprises an explicit or implicit obligation to accept instructions from the employer. The employee-statistician in the public sector may be restricted further by statutory regulations covering such matters as compulsory surveys and official secrecy.
7. Exhibiting Professional Competence
Statisticians shall seek to upgrade their professional knowledge and skill and shall maintain awareness of technological developments, procedures, and standards which are relevant to their field, and shall encourage their colleagues to do likewise. They also shall offer to do work or provide services which are within their professional competence, and shall not claim competence not possessed, and any professional opinion given shall be objective and reliable. They shall not commit to produce results when, in their judgment, conditions to succeed are not met.
Above all, statisticians should attempt to ensure that employers, clients, and funders appreciate the obligations that statisticians have, not only to them, but also to society at large, to subjects, to professional colleagues and to collaborators.
8. Maintaining Confidence in Statistics
In order to promote and preserve the confidence of the public, statisticians should ensure that they accurately and correctly describe their results, including the explanatory power of their data. It is incumbent upon statisticians to alert potential users of the results to the limits of their reliability and applicability.
9. Exposing and Reviewing Methods and Findings
Within the limits of confidentiality requirements, statisticians should provide adequate information to colleagues to permit their methods, procedures, techniques and findings to be assessed independently. Such assessments should be directed at the methods themselves rather than at the individuals who selected or used them.
10. Communicating Ethical Principles
In collaborating with colleagues and others in the same or other disciplines, it is necessary and important to ensure that the ethical principles of all participants are clear, understood, respected, and reflected in the undertaking.
Each of these principles stems from the notion that statisticians derive their status and certain privileges of access to data not only by virtue of their personal standing but also by virtue of their professional citizenship. In acknowledging membership of a wider statistical community, statisticians owe various obligations to that community and can expect consideration from it.
The reputation of statistics will inevitably depend less on what professional bodies of statisticians assert about their ethical norms than on the actual conduct of individual statisticians. In considering the methods, procedures, content and reporting of their inquiries, statisticians should therefore try to ensure that they leave a research field in a state which permits further access by statisticians in the future.
Statistical inquiries are frequently collaborative efforts among colleagues of different levels of seniority and from different disciplines. The reputations and careers of all contributors need to be taken into account. The statistician should also attempt to ensure that statistical inquiries are conducted within an agreed ethical framework, perhaps incorporating principles or conventions from other disciplines, and that each contributor's role is sufficiently defined. The World Medical Association's Declaration of Helsinki (1975), for instance, gives guidance to statisticians in the field of medicine.
A principle of all scientific work is that it should be open to scrutiny, assessment and possible validation by fellow scientists. Particular attention should be given to this principle when using computer software packages for analysis by providing as much detail as possible. Any perceived advantage of withholding details of techniques or findings, say for competitive reasons, needs to be weighed against the potential disservice of such an action to the advancement of statistical knowledge.
One of the most important but difficult responsibilities of the statistician is that of alerting potential users of their data to the limits of their reliability and applicability. The twin dangers of either overstating or understating the validity or generalisability of data are nearly always present. No general guidelines can be drawn except for a counsel of caution. Confidence in statistical findings depends critically on their faithful representation. Attempts by statisticians to cover up errors (see Ryten, 1981), or to invite over- interpretation, may not only rebound on the statisticians concerned, but also on the reputation of statistical institutions, as well as on statistics in general.
11. Bearing Responsibility for the Integrity of the Discipline
Statisticians should be aware of the intrusive potential of some of their work. They have no special entitlement to study all phenomena. The advancement of knowledge and the pursuit of information are not themselves sufficient justifications for overriding other social and cultural values.
Some forms of statistical inquiry appear to be more intrusive than others. For instance, statistical samples may be selected without the knowledge or consent of their members; contact may be sought with subjects without advance warning; questions may be asked which cause distress or offence; people may be observed or information collected without their knowledge; or information may be obtained from third parties. In essence, people may be inconvenienced or aggrieved by statistical inquiries in a variety of ways, many of which are difficult to avoid.
One way of avoiding inconvenience to potential subjects is to make more use of available data instead of embarking on a new inquiry. For instance, by making greater statistical use of administrative records, or by linking records, information about society may be produced that would otherwise have to be collected afresh. Although some subjects may have objections to the data's being used for a different purpose from that intended, they should not be adversely affected by such uses, provided that their identities are protected and that the purpose is statistical, not administrative.
As Cassell (1982) argues, people can feel wronged without being harmed by research: they may feel they have been treated as objects of measurement without respect for their individual values and sense of privacy. In many of the statistical inquiries that have caused controversy, the issue has had more to do with intrusion into subjects' private and personal domains, or with overburdening subjects by collecting 'too much' information, rather than with whether or not subjects have been harmed. By exposing subjects to a sense of being wronged, perhaps by the method of selection or by causing them to acquire self-knowledge that they did not seek or want, statisticians are vulnerable to criticism. Resistance to statistical inquiries in general may also increase.
Statistical inquiries involving the active participation of human subjects should be based as far as practicable on their freely given informed consent. Even if participation is required by law, it should still be as informed as possible. In voluntary inquiries, subjects should not be under the impression that they are required to participate; they should be aware of their entitlement to refuse at any stage for whatever reason and to withdraw data just supplied. Information that would be likely to affect a subject's willingness to participate should not be deliberately withheld.
The principle of informed consent from subjects is necessarily vague, since it depends for its interpretation on unstated assumptions about the amount of information and the nature of consent required to constitute acceptable practice. The amount of information needed to ensure that a subject is adequately informed about the purpose and nature of an inquiry is bound to vary from study to study. No universal rules can be framed. At one extreme it is inappropriate to overwhelm potential subjects with unwanted and incomprehensible details about the origins and content of a statistical inquiry. At the other extreme it is inappropriate to withhold material facts or to mislead subjects about such matters. The appropriate information requirement clearly falls somewhere between these positions but its precise location depends on circumstances. The clarity and comprehensibility of the information provided are as important as the quantity.
An assessment needs to be made of which items of information are likely to be material to a subject's willingness to participate. The statistician should consider not only those items that he or she regards as material, but those which the potential subject is likely to regard as such. Each party may well have special (and different) interests. As a means of supplementing the information selected, the statistician may choose to give potential subjects a declaration of their entitlement (see Jowell, 1981) which informs them of their right to information but leaves the selection of extra details in the subject's control.
Just as the specification of adequate information varies, so does the specification of adequate consent. A subject's participation in a study may be based on reluctant acquiescence rather than on enthusiastic co-operation. In some cases, the statistician may feel it is appropriate to encourage a sense of duty to participate in order to minimise volunteer bias. The boundary between tactical persuasion and duress is sometimes very fine and is probably easier to recognise than to stipulate. In any event, the most specific generic statement that can be made about adequate consent is that it falls short both of implied coercion and full-hearted participation.
On occasions, a 'gatekeeper' blocks access to subjects so that statisticians cannot approach them directly for their participation without the gatekeeper's permission. While respecting the gatekeeper's legitimate interests statisticians should still adhere to the principle of obtaining informed consent directly from subjects once they have gained access to them. In these cases, statisticians should not devolve their responsibility to protect the subject's interests onto the gatekeeper. They should also be wary of inadvertently disturbing the relationship between subject and gatekeeper.
The principle of informed consent is, in essence, an expression of belief in the need for truthful and respectful exchanges between statisticians and human subjects. It is clearly not a precondition of all statistical inquiry. Nonetheless, the acceptability of statistics depends increasingly not only on technical considerations but also on the willingness of statisticians to accord respect to their subjects and to treat them with consideration. Statisticians should attempt to ensure that subjects appreciate the purpose of a statistical inquiry, even when the subject's participation is required by law.
Qualifications to Informed Consent
On occasions, technical or practical considerations inhibit the achievement of prior informed consent. In these cases, the subjects' interests should be safeguarded in other ways. For example:
(a) Respecting rights in observation studies. In observation studies, where behavior patterns are recorded without the subject's knowledge, statisticians should take care not to infringe what may be referred to as the 'private space' of an individual or group. This will vary from culture to culture.
(b) Dealing with proxies. In cases where a 'proxy' is utilized to answer questions on behalf of a subject, say because access to the subject is uneconomic or because the subject is too ill or too young to participate directly, care should be taken not to infringe the 'private space' of the subject or to disturb the relationship between the subject and the proxy. Where indications exist or emerge that the subject would object to certain information being disclosed, such information should not be sought by proxy.
(c) Secondary use of records. In cases where a statistician has been granted access to, say, administrative or medical records or other research material for a new or supplementary inquiry, the custodian's permission to use the records should not relieve the statistician from having to consider the likely reactions, sensitivities and interests of the subjects concerned, including their entitlement to anonymity.
(d) Misleading potential subjects. In studies where the measurement objectives preclude the prior disclosure of material information to subjects, statisticians should weigh the likely consequences of any proposed deception. To withhold material information from, or to misinform subjects involves a deceit, whether by omission or commission, temporarily or permanently, which will face legitimate censure unless it can be justified.
A serious problem arises for statisticians when methodological requirements conflict with the requirement of informed consent. Many cases exist in which the provision of background information to subjects (say, about the purpose or sponsorship of a study), or even the process of alerting them to the fact that they are subjects (as in observation studies), would be likely to produce a change or reaction that would defeat or interfere with the objective of the measurement. These difficulties may lead statisticians to waive informed consent and to adopt either covert measurement techniques or deliberate deception in the interests of accuracy.
The principles above urge extreme caution in these cases and advise statisticians to respect the imputed wishes of subjects. Thus, in observation studies or in studies involving proxies, the principle to be followed is that mere indications of reluctance on the part of an uninformed or nonconsenting subject should be taken as a refusal to participate. Similarly, in the case of secondary use of records, statisticians should have regard to any obligations already owed to subjects. Any other course of action in these cases would be likely to demonstrate a lack of respect for the subject's interests and to undermine the relationship between statistician and subject.
Statistical inquiries involving deliberate deception of subjects (by omission or commission) are rare and extremely difficult to defend. Clear methodological advantages exist for deception in some psychological studies, for instance, where revealing the purpose would tend to bias the responses. But, as Diener and Crandall (1978) have argued 'science itself is built upon the value of truth'; thus deception by scientists will tend to destroy their credibility and standing. If deception were widely practised in statistical inquiries, subjects would, in effect, be taught not to 'trust those who by social contract are deemed trustworthy and whom they need to trust' (Baumrind, 1972).
Nonetheless, it would be as unrealistic to outlaw deception in statistical inquiry as it would be to outlaw it in social interaction. Minor deception is employed in many forms of human contact (tact, flattery, etc.) and statisticians are no less likely than the rest of the population to be guilty of such practices. It remains the duty of statisticians and their collaborators, however, not to pursue methods of inquiry that are likely to infringe human values and sensibilities. To do so, whatever the methodological advantages, would be to endanger the reputation of statistics and the mutual trust between statisticians and society which is a prerequisite for much statistical work.
For these reasons, where informed consent cannot be acquired in advance, there is a case, where practicable, for seeking it post hoc, once the methodological advantage - of covert observation, of deception, or of withholding information - has been achieved.
14.Protecting the Interests of Subjects
Neither consent from subjects nor the legal requirement to participate absolves the statistician from an obligation to protect the subject as far as possible against potentially harmful effects of participating. The statistician should try to minimise disturbance both to subjects themselves and to the subjects' relationships with their environment.
Harm to subjects may arise from undue stress through participation, loss of self-esteem, psychological injury or other side effects. Various factors may be important in assessing the risk-benefit ratio of a particular inquiry, such as the probability of risk, the number of people at risk, the severity of the potential harm, the anticipated utility of the findings, few of which are usually quantifiable (see Levine, 1975).
When the probability or potential severity of harm is great, statisticians face a more serious dilemma. A statistician may, for instance, be involved in a medical experiment in which risks to subjects of some magnitude are present. If volunteers can be found who have been told of the risks, and if the statistician is convinced of the importance of the experiment, should he or she nonetheless oppose the experiment in view of the risks? In these circumstances, probably the best advice is to seek advice - from colleagues and others, especially from those who are not themselves parties to the study or experiment.
The interests of subjects may also be harmed by virtue of their membership of a group or section of society (see Clause 1.1). So statisticians can rarely claim that a prospective inquiry is devoid of possible harm to subjects. They may be able to claim that, as individuals, subjects will be protected by the device of anonymity. But, as members of a group or indeed as members of society itself, no subject can be exempted from the possible effects of decisions based on statistical findings.
15. Maintaining Confidentiality of Records
Statistical data are unconcerned with individual identities. They are collected to answer questions such as 'how many?' or 'what proportion?', not 'who?'. The identities and records of co-operating (or non- cooperating) subjects should therefore be kept confidential, whether or not confidentiality has been explicitly pledged.
16. Inhibiting Disclosure of Identity
Statisticians should take appropriate measures to prevent their data from being published or otherwise released in a form that would allow any subject's identity to be disclosed or inferred.
There can be no absolute safeguards against breaches of confidentiality, that is, the disclosure of identified or identifiable data in contravention of an implicit or explicit obligation to the source. Many methods exist for lessening the likelihood of such breaches, the most common and potentially secure of which is anonymity. Its virtue as a security system is that it helps to prevent unwitting breaches of confidentiality. As long as data travel incognito, they are more difficult to attach to individuals or organisations.
There is a powerful case for identifiable statistical data to be granted 'privileged' status in law so that access to them by third parties is legally blocked in the absence of the permission of the responsible statistician (or his or her subjects). Even without such legal protection, however, it is the statistician's responsibility to ensure that the identities of subjects are protected.
Anonymity alone is by no means a guarantee of confidentiality. A particular configuration of attributes can, like a fingerprint, frequently identify its owner beyond reasonable doubt. So statisticians need to counteract the opportunities for others to infer identities from their data. They may decide to group data in such a was as to disguise identities (see Boruch & Cecil, 1979) or to employ a variety of available measures that seek to impede the detection of identities without inflicting very serious damage to the aggregate dataset (see Flaherty, 1979). Some damage to analysis possibilities is unavoidable in these circumstances, but it needs to be weighed against the potential damage to the sources of data in the absence of such action. (See Finney, 1984).
The widespread use of computers is often regarded as a threat to individuals and organisations because it provides new methods of disclosing and linking identified records. On the other hand, the statistician should attempt to exploit the impressive capacity of computers to disguise identities and to enhance data security.