Background Documentation and Bibliography: ISI Declaration on Professional Ethics

In this document: 

  1. Historical Commentary 
  2. Codes of Ethics: Selected Statistical Associations 
  3. Codes of Ethics: Selected Non-statistical Associations 
  4. Bibliography


The following discussion reflects an extensive dialog among the architects of the initial Declaration on Professional Ethics from 1985. It is archived here for reference as much of its value remains relevant. 

In reflecting on or in reacting to an Ethical Principle, the statistician must be cognizant of the fact that, in many cases, actions taken will reflect more than a single principle. For one example, the statistician must be sensitive to the possible consequences of the work product, given the knowledge that society's entitlement to know about its collective characteristics sometimes conflicts with the individual's entitlement to protect his or her privacy (or that of a group or community). Many such examples could be cited to illustrate the complexity and interrelationships of what, at first, may appear to be simple ethical issues.

1. Pursuing objectivity 

Statisticians should pursue objectivity without fear or favor, only selecting and using methods designed to produce the most accurate results, consistent with accepted international practices. They should present 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.

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.

2. Clarifying obligations and roles 

The respective obligations of employer, client, or funder, and statistician in regard to their roles and responsibility that might raise ethical issues 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.

Statisticians should clarify in advance the respective obligations of employer, client, or funder and statistician; they should, for example, refer the employer or funder to the relevant parts of a professional code to which they adhere. Reports of the findings should (where appropriate) specify their role.

3. Assessing alternatives impartially 

Available methods and procedures 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 should consider the available methods and procedures for addressing a proposed inquiry and should provide the funder or employer with an impartial assessment of the respective merits and demerits of alternatives.

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.

4. Conflicting interests 

No generic formula or guidelines exist for assessing the likely benefit or risk of various types of statistical inquiry. Nonetheless, the statistician must be sensitive to the possible consequences of his or her work, in the knowledge that society's entitlement to know about its collective characteristics sometimes conflicts with the individual's entitlement to protect his or her privacy.

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 low. 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 misleading.

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.

Statisticians should not accept contractual conditions that are contingent upon a particular outcome from a proposed statistical inquiry.

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.

Statisticians depend upon the confidence of the public. They should in their work attempt to promote and preserve such confidence without exaggerating the accuracy or explanatory power of their data.

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, in the exercise of their science and scholarship, are subject to the general moral rules of scientific and scholarly conduct: they should not deceive or knowingly misrepresent (i.e., fabricate, falsify, or plagiarize), or attempt to prevent reporting of misconduct or obstruct the scientific/scholarly research of others. 

Further, they should publicly acknowledge assistance received in research and preparation of their work, give appropriate credit for co-authorship or contribution, encourage publication by colleagues or students, and compensate justly those who assist or participate in professional activities.

12.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 minimize 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 selfesteem, 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.

Avoiding Undue Intrusion 

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.

Ensuring Informed Consent

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.

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.

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 way 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.


1. UN: Principles Governing International Statistical Activities es_stat_activities.htm 

2. UN: Fundamental Principles of Official Statistics

3. European Statistics Code of Practice

4. American Statistical Association Ethical Guidelines for Statistical Practice

5. ASA: Privacy, Confidentiality, and Data Security

6. AAPOR: Code of Professional Ethics and Practices

7. WAPOR Code of Professional Ethics and Practices

8. European Society for Opinion and Marketing Research (ESOMAR)

9. Royal Statistical Society Code of Conduct

10. Respect Project: Code of Practice for Socio-Economic Research

11. Statistical Society of Canada: Code of Ethical Statistical Practice

12. Mexican Association of Market Research and Public Opinion (AMAI) (in Spanish)

13. ACM Software Engineering

16. Misc: Comparative Table of Ethical Practices, for selected professional organizations 

AMSTAT Article: Making Statistical Ethics Work for You, of Course


1. American Sociological Association

2. Public Health Leadership Society

3. Society for Public Health Education

 4. World Medical Association

5. Medical Research Council (UK)

 6. American Political Science Association

 7. American Anthropological Association

 8. Association for Computing Machinery

 9. ACM Software Engineering

 10. Online


Ethics Related Publications, by Ethical Principle

1 Quality Management in Statistical Organization: Discussion. Clark, Cynthia Z. et al. JSM 2005. Principle: 4/8 

2 The unpleasant placebo? Senn, Stephen. Chance, JSM2002. Principle: 4 

3 Statistics and medical experimentation. Meier, Paul. Biometrics 1975. Principle: 8 

4 Ethics, Confidentiality, and Data Dissemination. Paper at ISI - 5th Session, Sydney 2005. Habermann, Hermann. 2005. Principle: 1-12 

5 The Thin Line between Statistical and public Information in Scandinavia, Paper at Invited Paper session 66. ISI 53rd Session Seoul - Ljones, Olav. 2001. Principle: 6 

6 Developing Saami statistics in Norway challenges and possibilities. IAOS/ISI session in New Zealand. Pettersen, Torunn and Even Hydahl. April 2005. Principle: 11 

7 IAOS Satellite Meeting on "Statistics for Small Populations including Indigenous and Small Domain Populations". IAOS. Pettersen, Torunn and Even Hydahl. 2005. Principle: 11 

8 Official Statistics and Statistical Ethics: Selected Issues. Paper presented at ISI 55th Session 2005. Sydney. Seltzer, William. 2005. Principle: 1-12 

9 Managing Statistical Confidentiality and Micro data Access Core Principles and Good Practice Guidelines, paper presented by Dennis Trewin, Chairman ECE, Geneva, June 2005, CERS Task Force on Confidentiality and Microdata, CES/2005/5. 2005. Principle: 12 

10 On the ethical aspects of the testimony of statisticians in court. Gehan, E. A. Statistical Methods in Medical Research 2002. Principle: 4/10 

11 The ethics of consulting for the tobacco industry. Rubin, D. B. Statistical Methods in Medical Research 2002. Principle: 4/10 

12 IRB committees: Balancing medical policy, ethics and statistics. Efird, Jimmy Thomas. ASA Proceedings of the Joint Statistical meetings 2001. Principle: 4/10 

13 Ethical challenges at the beginning of the millennium. Steinberg, Karen K. Statistics in Medicine 2001. Principle: 4/10 

14 Ethics of medical research in developing countries. The role of international codes of conduct. Hutton, J. L. Statistical Methods in Medical Research, 9 (3) 2000. Principle: 4/10 

15 Ethics and practice: Alternative designs for phase III randomized clinical trials. Palmer, Christopher R., and Rosenberger, William F. Controlled Clinical Trials 1999. Principle: 4/10 

16 Statistical ethical issues in human experimentation. Cobo, E. Questiio 1999. Principle: 4/10

17 Ethics and the expert witness: Statistics on trial. Fienberg, Stephen E. Journal of the Royal Statistical Society, Series A, General 1997.  Principle: 4/10 

18 What and where are statistical ethics? Gardenier, John S. ASA Proceedings of the Section on Statistical Education 1996.  Principle: 4/10 

19 Ethical aspects of statistical practice. Finney, David J. Biometrics 1991.  Principle: 4/10 

20 Critical Values: Connecting, Ethics, Service Learning, and Social Justice to Lift our World. Lesser, Lawrence M. JSM 2005.  Principle: 1/10 

21 Clinical Trials Data Monitoring Committees: The Who, What, When and Why of an Unmasking. Lindblad, Annes. JSM 2004.  Principle: 12 

22 Ethical aspects of survey research. Cunliffe, Stella Y., and Goldstein, H. Applied Statistics 1979.  Principle: 8/10 

23 Determining the Level of Statisticians participation in Canadian Based Research Ethics Committees. Thabane, Lehana, Childs, Aaron and Lafontaine, Amanda. JSM 2003.  Principle: 1/4 

24 The AAPOR code of professional ethics and practices. Sudman, Seymour. ASA Proceedings of the Section on Survey Research Methods 1988.  Principle: 1/4 

25 Ethical guidelines for statistical practice: Report of the ad hoc committee on professional ethics (with discussion. ASA Ad Hoc Committee on Professional Ethics. The American Statistician 1983.  Principle: 1/4 

26 Ethical issues in the social sciences. Hobbs, Nocholas. International Encyclopedia of Statistics, Volume 1 1977.  Principle: 1/4 

27 The code of the scientist and its relationship to ethics. Cournand, Andre. Science 1977.  Principle: 1/4 

28 Ethical and legal issues of social experimentation. Rivlin, Alice M. (ed), and Timpane, P. Michael (ed). 1975.  Principle: 1/4 

29 Social surveys and the responsibilities of statisticians. Zernach, Rita. The American Statistician 1969.  Principle: 1/4 

30 Statistics and Counterterrorism: The Role of Law, Policy and Ethics. Seltzer, William. Conference on Statistics and Counterterrorism (CSC) 2004.  Principle: 4 

31 The Institutional Review Board: Friend or Foe in a Graduate Students Career. Tomasic, Terry, et at. JSM 2004.  Principle: 4 

32 The Promise and Pitfalls of Data Mining: Ethical Issues. Seltzer, William. JSM 2005.  Principle: 4 

33 Ethics, Confidentiality, and Data Dissemination. Haberman, Hermann. Presented at ISI Sydney, Australia, April 2005.  Principle: 4 

34 Sanctified Snake Oil: Ideology, junk science, and social work practice. Sarnoff, Susan Kiss. Families in Society v. 80 no.4 (July/August 1999).  Principle: 4 

35 Discussion of emerging ethical issues in statistical publishing. Banks, David. Proceedings of the JSM 2002.  Principle: 4

36 NCES and the Patriot Act: an early appraisal of facts and issues. Seltzer, William, and Anderson, Margo. ASA Proceedings of the JSM 2002.  Principle: 4 

37 The collision of government, ethics, and statistics: Case studies and comments. Banks, David. ASA Proceedings of the section on Government Statistics and Section on Social Statistics 1999.  Principle: 4 

38 Information privacy: Redefining the legal and ethical framework when the physical boundaries disappear. Gates, Gerald W. ASA Proceedings of the Social Statistics Section 1997.  Principle: 4 

39 Design, analysis, and ethics. Heaney, Robert Proulx, Creighton, John A., and Dougherty, Charles J. 1987.  Principle: 4 

40 An Example of Utilizing Data Analysis for Assessing Courses Within a Math General Education Curriculum. Todd, Charles S. JSM 2005.  Principle: 4 

41 Statistics & Counterterrorism: The Role of Law, Policy and Ethics. Seltzer, William. CSC 2004.  Principle: 4 

42 Improving Quality and Access to Federal Data: Memorial Session in Honor of Pat J. Doyle. Shipp, Stephanie. JSM 2005.  Principle: 1 

43 The Federal Committee on Statistical Methodology: Past Accomplishments, Present Activities, and Future Directions. HarrisKojetin; Brian; and Wallman, K. JSM 2005.  Principle: 1 

44 Using Privacy Impact Assessments to Implement Data Stewardship Principles and Practices. Martinex, Shelly. JSM 2003.  Principle: 1 

45 Standards and Guidelines for Statistical Surveys. U.S. Office of Management and Budget, September 2006.  Principle: 1 

46 Proposed Implementation Guidance for Title V of the E-Government Act, Confidential Information Protection and Statistical Efficiency Act of 2002 (C(PSEA). U.S. Office of Management and Budget, October 2006.   Principle: 1 

47 Making a difference: A role for the responsible international statistician? Lievesley, Denise. The Statistician 2001.  Principle: 1 

48 Statistical science and effective scientific communication. Finney, David J. Journal of Applied Statistics 1995.  Principle: 1

49 The codification of statistical ethics. Jowell, Roger. Journal of Official Statistics 1986.  Principle: 1 

50 Studying certification for statisticians. Boen, James R. The American Statistician 1990.  Principle: 8 

51 Grave scientific and ethical issues in ASA sponsorship of a symposium. Bross, Irwin D. The American Statistician 1986.  Principle: 8 

52 Federal Data Sharing Requirements and Issues (Contributions to be made by Statistics, Survey Research, and Related Disciplines). deWolf, Virginia. JSM 2004.  Principle:  8 

53 An Overview of the Quality Control Programs for the NCHS Harris, KW. JSM 2003. Principle: 8

54 Ethics and Sample Size. Bacchetti, Peter. American Journal of Epidemiology v.161 no.2 (January 15, 2005). Principle:  8 

55 The responsible referee. Finney, David J. Biometrics 1997. Principle: 8 

56 Sequential allocation for an estimation problem with ethical costs. Woodroofe, Michael, and Hardwick, Janis. The Annals of Statistics 1990. Principle: 8 

57 Ethics in official statistics (Italian). Colombo, B. Statistica 1990. Principle: 8 

58 The need for and structure of standards of conduct for survey research practitioners. ONeill, Harry W. ASA Proceedings of the Section on Survey Research Methods 1988. Principle: 8 

59 Science and values in the regulatory process. Ashford, Nicholas A. Statistical Science 1988. Principle: 8 

60 Science and values in the regulatory process. Ashford, Nocholas A. Statistical Science 1988. Principle: 8 

61 The questioning statistician. Finney, D. J. Statistics in Medicine 1982. Principle: 8 

62 Federal Statistics Users Conference Committee on Integrity of Federal Statistics: Maintaining the professional integrity of Federal statistics. American Statistical Association. The American Statistician 1973. Principle: 8 

63 A question of ethics. Gibbons, Jean D. The American Statistician 1973. Principle: 8 

64 Code of professional conduct. Deming, W. Edwards. Sankhya, Series B, Indian Journal of Statistics 1966. Principle: 8 

65 Principles of professional statistical practice. Deming, W. Edwards. The Annals of mathematical Statistics 1965. Principle: 8 

66 Training of statisticians in diplomacy to maintain their integrity. Freeman, William W. K. The American Statistician 1963. Principle:  8 

67 Report of the Ad Hoc Committee to Explore Opinion on Standards. Freeman, William W. K. The American Statistician 1956. Principle: 8 

68 Statistical standards. Court, Andrew T. The American Statistician 1952. Principle: 8 

69 The statistician and his conscience. Brown, Theodore H. The American Statistician 1952. Principle: 8 

70 Critical Values: Connecting, Ethics, Service Learning, and Social Justice to Lift out World. Lesser, Lawrence M. JSM 2005. Principle:  8 

71 Research methods Short Course Curriculum for Residents Based on an Empirical Problem Solving Approach. Rosychuk, Rhonda J. JSM 2005. Principle:  8 

72 Curb Stoning in Survey Research and Required Reporting to the office of Research Integrity. Price, Alan R. JSM 2004. Principle: 9 

73 Do Disclosure Controls to Protect Confidentiality Degrade the Quality of the Data? Kaufman, Steve; Roey, Shep; Seastrom, Marilyn. JSM2005. Principle: 9 

74 Internal Quality Audits at the Portuguese National Statistical Institute. Zilhao, Maria Joao. JSM 2005. 9 75 Modeling and Quality of Masked Microdata. Winkler, William E. Principle: 9

75 Modeling and Quality of Masked Microdata. Winkler, William E. JSM2005. Principle: 9

76 Monitoring Data Quality at a Federal Statistical Agency: NCES. Seastrom, Marilyn. JSM 2005. Principle:  9 

77 Research Methods Short Course Curriculum for Residents Based on an Empirical Problem Solving Approach. Rosychuk, Rhonda J. JSM 2005. Principle: 9 

78 Standards for Surveys at Statistics Canada. Brackstone, G. JSM 2003. Principle: 9 

79 Striving for Data Quality: Pat Doyles Legacy at the US Census Bureau. Bowie, Chester E.; Moore, Jeffrey C. JSM 2005. Principle: 9 

80 Survey Quality Issues During the Last 50 Years and Some Observations. Lyberg, Lars. JSM 2003. Principle: 9 

81 Survey Response Rate Reporting in the Professional Literature. Johnson, Timothy. JSM 2003. Principle: 9 

82 The Quality Framework: A Guide for Measuring Quality at NCHS. Harris, Kenneth W. JSM 2004. Principle: 9 

83 Updating Federal Standards for Statistical Surveys. Tupek, Alan; et al. JSM 2004. Principle: 9 

84 Statistical review by research ethics committees. Williamson, P., Hutton, J. L., Bliss, J., Blunt, J., Campbell, M. J., and Nicholson, R. Journal of the Royal Statistical Society, Series A, General, 163 (1) 2000. Principle: 9 

85 Perspectives on scientific misconduct and fraud in clinical trials. George, Stephen L. Chance, New Directions for Statistics and Computers 1997. Principle: 9 

86 The aftermath of falsified data in breast cancer trials. Harrington, David. Chance, New Directions for Statistics and Computers 1997. Principle: 9 

87 Reflections on the NSABP affair. OFallon, Judith Rich. Chance, New Directions for Statistics and Computers 1997. Principle: 9 

88 Analysing non-compliance in clinical trials: Ethical imperative or mission impossible? Goetghebeur, Els J. T. and Shapiro, Stanley H. Statistics in Medicine 1996. Principle: 9 

89 Bayesian methods and ethics in a clinical trial design, John Wiley and Sons. Kadane, Joseph B. 1996. Principle: 9 

90 Presenting ethical issues in an introductory statistics course. Berenson, Mark L. ASA Proceedings of the Section on Statistical Education 1995. Principle: 9 

91 A modified bandit as an approach to ethical allocation in clinical trials. Hardwick, J. P. Adaptive Designs 1995. Principle: 9 

92 Ethics and statistics in clinical research: Towards a more comprehensive examination. Freedman, Benjamin, and Shapiro, Stanley H. Journal of Statistical Planning and Inference 1994. Principle: 9 

93 Early stopping rules Clinical perspectives and ethical considerations. Baum, M., Houghton, J., and Abrams, K. Statistics in Medicine 1994. Principle: 9 

94 Comment on Early stopping rules Clinical perspectives and ethical considerations. Burke, G. Statistics in Medicine 1994. Principle: 9

95 Statistical and ethical issues in the design and conduct of phase I and II clinical trials of new anticancer agents. Ratain, Mark J., Mick, Rosemarie, Schilsky, Richard L., and Siegler, Mark. Journal of the National Cancer Institute 1993. Principle: 9 

96 Data monitoring and interim analyses in the pharmaceutical industry: Ethical and logistical considerations. Rockhold, Frank W., and Enas, Gregory G. Statistics in Medicine 1993. Principle: 9 

97 Statistical and ethical issues in monitoring clinical trials. Pocock, Stuart J. Statistics in Medicine 1993. Principle: 9 

98 Identification of key attributes, gap analysis and simulation techniques in forecasting market potential of ethical pharmaceutical products. Kontzalis, Panos. International Journal of Forecasting 1992. Principle: 9 

99 Introducing new treatments for cancer: practical, ethical, and legal problems, John Wiley and Sons. Williams, C. J. 1992. Principle: 9 

100 False Claims Act. Bross, Irwin D. The American Statistician 1991. Principle: 9 

101 Ethics in quality. Mundel, August B. Marcel Dekker Inc. 1991. Principle: 9 

102 Ethics and statistics in randomized clinical trials. Royall, Richard M. Statistical Science 1991. Principle: 9 

103 Comment on Ethics and statistics in randomized clinical trials. Bartlett, Robert H., and Cornell, Richard G. Statistical Science 1991. Principle: 9 

104 Comment on Ethics and statistics in randomized clinical trials. Byar, David P., Statistical Science 1991. Principle: 9 

105 Comment on Ethics and statistics in randomized clinical trials. Dupont, William D. Statistical Science 1991. Principle: 9 

106 Comment on Ethics and statistics in randomized clinical trials. Levine, Robert J. Statistical Science 1991. Principle: 9 

107 Comment on Ethics and statistics in randomized clinical trials. Lindley, Foster. Statistical Science 1991. Principle: 9 

108 Comment on Ethics and statistics in randomized clinical trials. Simes, R. John. Statistical Science 1991. Principle: 9 

109 Comment on Ethics and statistics in randomized clinical trials. Zelen, M. Statistical Science 1991. Principle: 9 

110 Reply to comments on Ethics and statistics in randomized clinical trials. Royall, Richard M. Statistical Science 1991. Principle: 9 

111 Investigating therapies of potentially great benefit: ECMO. Ware, James H. Statistical Science 1989. Principle: 9 

112 The search for optimality in clinical trials. Armitage, P. International Statistical Review 1985. Principle: 9 

113 Sequential medical trials with ethical cost. Chernoff, Herman, and Petkau, A. John. Proceedings of the Berkeley Conference in Honor of Jerzy Neyman and Jack Kiefer 1985. Principle: 9

114 Incorporating scientific, ethical and economic considerations into the design of clinical trials in the pharmaceutical industry: A sequential approach. Lai,T.L. Communications in Statistics, Part A Theory and Methods 1984. Principle: 9 

115 Ethical guidelines for statistical practice: A historical perspective. Ellenberg, Jonas H. The American Statistician 1983. Principle: 9 

116 Ethical aspects of clinical trials. Lebacqz, Karen. Clinical Trials. Issues and Approaches 1983. Principle: 9 

117 Critical reflections on clinical trials. Ruemke, Chr. L. Statistics in Medicine 1983. Principle: 9 

118 Please dont squeeze the statistics. Cullen, Francis J. ASQC Technical Conference Transactions 1982. Principle: 9 

119 The randomized controlled clinical trial: Scientific and ethical bases. Spodick, David H. American Journal of Medicine 1982. Principle: 9 

120 Is it ethical not to conduct a prospectively controlled trial of adjuvant chemotherapy in osteosarcoma? Lange, Beverly, and Levine, Arthur S. Cancer Treatment Reports 1982. Principle: 9 

121 Clinical trials: Exploring ethical, legal, and psychological issues. Mike, Valerie, Annas, George J., Cassell, Eric J., Holland, Jimmie C. B., and Levine, Robert J. Statistics in Medical Research. 1982. Principle: 9 

122 Protecting the scientific integrity of a clinical trial: Some ethical dilemmas. Howard, Jan, and Friedman, Lawrence. Clinical Pharmacology and Therapeutics 1981. Principle: 9 

123 Terminating a trial: The ethical problem. Meier, Paul. Clinical Pharmacology and Therapeutics 1979. Principle: 9 

124 Terminating a long-term clinical trial. Klimt, Christian R., and Canner, Paul L. Clinical Pharmacology and Therapeutics 1979. Principle: 9 

125 Decision theory and social ethics. Gottinger, Hans W. (ed), and Leinfellner, Werner (ed). 1978. Principle: 9 

126 The ethics of biomedical experimentation. Rowsell, Harry C. The Future of Animals, Cells, Models and Systems in Research, Development, Education and Testing 1977. Principle: 9 

127 Clinical trials: Methods and ethics are debated. Kolata, Gina Bari. Science 1977. Principle: 9 

128 A parley on quality control ethics. Banerjee, S. K. IAPQR Transactions, Journal of the Indian Association for Productivity, Quality and Reliability 1976. Principle: 9 

129 Critical analysis of the statistical and ethical implications of various definitions of test bias. Hunter, John E., and Schmidt, Frank L. Psychological Bulletin 1976. Principle: 9

130 The effect of ethical design considerations on statistical analysis. Lindley, D. V. Applied Statistics 1975. Principle: 9 

131 Bayesian Meta-Analysis on Drug-Eluting Stent Trials. Yu, Yongyi (Alan). JSM 2005. Principle: 9 

132 Efficiency Issues with Cross-Trial Estimation of Control Effect in ActiveControl Trials. Sankoh, Abdul J. JSM 2005. Principle: 9 

133 Optimizing the Use of Micro-Data: An Overview of the Issues. Lane, Julia. JSM 2005. Principle: 9 

134 The Promise and Pitfalls of Data Mining: Ethical Issues. Seltzer, William. JSM 2005. Principle: 9 

135 Clinical Ethics Consultation. Anderson, Emily; Badro, Valerie; Katz, Barry; Tomazic, Terry. JSM 2005. Principle: 10 

136 Ethical Issues in Being an Expert Witness. Kadane, Joseph. JSM 2004. Principle: 10 

137 Ethics, data-dependent designs, and the strategy of clinical trials: Time to start learning-as-we-go? Palmer,C.R. Statistical Methods in Medical Research 2002.  Principle: 10 

138 Ethical considerations concerning treatment allocation in drug development trials. Senn, S. Statistical Methods in Medical Research 2002. Principle: 10 

139 Ethical issues in oncology biostatistics. Thall, Peter F. Statistical Methods in Medical Research 2002. Principle: 10 

140 Ethical issues in clinical trials in developing countries. Brody, Baruch A. Statistics in Medicine 2002. Principle: 10 

141 Ethical statistics and statistical ethics: The experience of creating an interdisciplinary module. Lesser, LawrenceM. ASA Proceedings of the Joint Statistical Meetings 2001. Principle: 10 

142 Optimal adaptive designs for binary response trials. Michelle L. Biometrics 2001. Principle: 10 

143 Surveys and polling: Ethical aspects. Singer, E. International Encyclopedia of the Social and Behavioral Sciences 2001. Principle: 10 

144 Are distinctive ethical principles required for cluster randomized controlled trials? Hutton, J. L. Statistics in Medicine 2001. Principle: 10 

145 Experiences of a biostatistician on a U.K. research ethics committee. Vail, Andy. Statistics in Medicine 1998. Principle: 10 

146 Logrank, play the winner, power and ethics. Hallstrom, Al, Brooks, Maria More, and Peckova, Monika. Statistics in Medicine 1996. Principle: 10 

147 A statisticians approach to ethical guidelines: Selected methodologies for review and evaluation. Gardenier, Turkan K. ASA Proceedings of the Section on Statistical Education 1995. Principle: 10

148 Statistical ethics. Quinn, Linda M. The Magazine for Students of Statistics 1995. Principle: 10 

149 The maintenance of ethical principles in marketing research. Dutka, Solomon, and Frankel, Lester R. ASA Proceedings of the Section on Survey Research Methods 1994. Principle: 10 

150 Statistical values, quality, and certification. Imrey, Peter B. The American Statistician 1994. Principle: 10 

151 Ethical treatments. Good, I. J. Journal of Statistical Computation and Simulation 1978.  Principle: 10 

152 Symposium review: Medical research: Statistics and ethics. May, Ron A. Jurimetrics Journal 1978. Principle: 10 

153 Statistical ethics. Goldstein, Harvey, and Kanji, Gopal. Bulletin in Applied Statistics 1977. Principle: 10 

154 Old problems, new challenges. Mike, Valerie, and Good, Robert A. Science 1977. Principle: 10 

155 Statistics and ethics in surgery and anesthesia. Gilbert, John P., McPeek, Bucknam, and Mosteller, Frederick. Science 1977. Principle: 10 

156 Acquiring new information while retaining old ethics. Herbert, Victor. Science 1977. Principle: 10 

157 Scandal in the heavens: Renowned astronomer accused of fraud. Wade, Nicholas. Science 1977. Principle: 10 

158 The statisticians responsibilities. Frankel, Lester R. Journal of the American Statistical Association 1976. Principle: 10 

159 Data Acquisition Issues in a Survey of Health care Professionals in Hospitals and Health Departments Invited to Participate in the U.S. Small Pox Immunization Program. Burke, Brian J.; Evans, Brian M.; Levy, Paul S. JSM 2005. Principle: 12 

160 The politics and ethics of fieldwork. Punch, Maurice. Sage Publications Inc. 1986. Principle: 12 

161 Interviewing in social research. Kahn, Robert L., and Cannell, Charles F. International Encyclopedia of Statistics, Volume 1 (1977). Principle: 12 

162 Hospice, HIPAA< and Hope: Survey Research with the Terminally Ill. Kovach, Terri. AAPOR 2005. Principle: 12 

163 How Could they Ever, Ever Persuade You? Are Some Refusals Easier to Convert than Others? Moon, Nick; Rose, Nickie; Steel, Nikki. AAPOR 2005. Principle: 12 

164 A New Method to Identify the Minimum Effective Dose. Lee, Chu-In Charles; Liu, Lin; Peng, Jianan. JSM 2005. Principle: 12 

165 Noninferiority Hypothesis with Binary endpoints. Ng, Tie-Hua. JSM 2005. Principle: 12 

166 Statistical Design and Analysis Issues with Pharmacogenomic Drugdiagnostic Co-development. Pennello, Gene A.; Vishnuvajjala, Lakshmi. JSM 2005. Principle: 12

167 Development and Testing of Informed Consent Questions to Link Survey Data with Administrative Records. Bates, Nancy. JSM AAPOR Annual Meeting 2005. Principle: 12 

168 Patterns of consent in Epidemiologic Research: Evidence from over 25,000 responders. Dunn, Kate M. American Journal of Epidemiology v.159 no.11 (June 1, 2004). Principle: 12 

169 Use of human subjects in experimentation: Informed consent. Knepper, Janet D. Journal of the American Medical Record Association 1982.  Principle: 12 

170 The random response method: A valid and ethical indicator of the truth in reactive situations. Shotland, R. L., and Yankowski, L. D. Personality and Social Psychology Bulletin 1982.  Principle:12 

171 Development and Testing of Informed Consent Questions to Link Survey Data with Administrative Records. Bates, Nancy. AAPOR ASA Section on Survey Research Methods 2005. Principle: 12 

172 Acquisition and Protection of Administrative Records: A Census Bureau Perspective. Blumerman, Lisa; Mervin, Patricia. JSA 2005. Principle: 12 

173 An Overview of the Confidential Information Protection and Statistical Efficiency Act of 2002 (CIPSEA). Martinex, Shelly. JSM 2003. Principle: 12 

174 An Update on Statistical Disclosure Avoidance Methodologies for Tabular and Microdata Files. Bournazian, Jacob D. JSM 2005. Principle: 12 

175 Panel on Privacy and Data Use in the New Technological Environment Alvey, Wendy; Barabba, Vincent; Blumerman, Lisa; Gates, Gerald W. Kincannon, Clarles Louis; Martinex, Shelly Wilkie. JSM 2005. Principle: 12 

176 Privacy and the Statistician: What do we need to know to Certify Nondisclosure? Zaslavsky, Allen M. JSM 2004. Principle: 12 

177 Choice of control group in therapeutic device trials. Kogut, Sarah J. H. ASA Proceedings of the JSM 2002. Principle: 12 

178 The protection of identity in statistical activities: Laws, ethics and the attitude of the general population as seen from an international perspective (German). Rapaport, Edmund. Jahrbcher fr Nationalkonomie und Statistik 1987. Principle: 12 

179 Ethical issues in access to and linkage of publicly collected data. Jabine, Thomas B. ASA Proceedings of the Section on Survey Research Methods 1986. Principle: 12 

180 Ethical issues in access to and linkage of publicly collected data. Gastwirth, Joseph L. ASA Proceedings of the Section on Survey Research Methods 1986. Principle: 12 

181 Ethical issues in access to and linkage of publicly collected data. Jacobs, Eva E. ASA Proceedings of the Section on Survey Research Methods 1986. Principle: 12 

182 Ethical issues in access to and linkage of publicly collected data. Butz, William P., and Gates, Gerald W. ASA Proceedings of the Section on Survey Research Methods 1986. Principle: 12

183 Ethical issues in access to and linkage of publicly collected data. Pearson, Robert W. ASA Proceedings of the Section on Survey Research Methods 1986.Principle:  12 

184 Disclosure Avoidance and Data Mining: A Perspective of a Federal Statistical Agency. Hawala, Sam. JSM 2005. Principle: 12 

185 Disclosure Risk Assessment for Microdata. Steel, Philip M. JSM 2004. Principle: 12 

186 Disclosure Risks with Regression Models: Some Further Results. Reznick, Arnold; Riggs, T. Lynn. JSM 2004. Principle: 12 

187 Discussion Implications of Recent e-Government Legislation. Thabane, Lehana. JSM 2003. Principle: 12 

188 From Privacy Impact Assessment (PIA) to Policy. Blumerman, Lisa. JSM2004. Principle: 12 

189 Hospice, HIPPA, and Hope: Survey Research with the Terminally Ill. Kovach, Terri. JSM, AAPOR Annual Meeting 2005. Principle: 12 

190 Incorporating HIPAA. Privacy Rule into Medical Records Surveys. Burt, Catherine W. JSM 2004. Principle: 12 

191 Multiple and Probabilistic Swapping of Categorical Keys for Statistical Disclosure Limitation in Microdata. Liu, Fang. JSM 2005. Principle: 12 

192 Optimizing the Use of Micro-Data: An Overview of the Issues. Lane, Julia. JSM 2005. Principle: 12 

193 Use of an Audit Program to Improve Confidentiality Protection of Tabular Data at BLS. Powers, Randall; Cohen, Stephan. JSM 2004. Principle: 12 

194 The dissemination of data among statistical offices and data access for research purposes: the case of Italy. Biggeri, Luigi. ASA Proceedings of the JSM 2002. Principle: 12 

195 Ethics and efficacy in releasing official statistics to the public and data users. Gordon, Nancy. ASA Proceedings of the JSM 2002. Principle: 12 

196 Confidentiality and the future of the U.S. statistical system. Duncan, Joseph W. The American Statistician 1976. Principle: 12 

197 Acquisition and Protection of Administrative Records: A Census Bureau Perspective. Blumerman, Lisa; Melvin, Patricia. JSM 2005. Principle: 12 

198 Panel on Privacy and Data Use in the new Technological Environment. Alvey, Wendy; Barabba, Vincent; Blumerman, Lisa; Gates, Gerald W.; Kincannon, Charles Louis; Martinex, Shelly Wilkie. JSM 2005. Principle: 12