Statement of Commitment to Scientific Integrity

by Principal Statistical Agencies

Our Nation relies on the flow of objective, credible statistics to support the decisions of governments, 

businesses, households, and other organizations. Any loss of trust in the integrity of the Federal

statistical system and its products can foster uncertainty about the validity of measures our Nation uses 

to monitor and assess performance and progress.

Federal statistical agencies (or units) whose principal function is the collection, analysis, and 

dissemination of information for statistical purposes have set for themselves a high standard of scientific 

integrity. The following agencies are designated as “principal statistical agencies1

” –

Bureau of Economic Analysis (Commerce Department)

Bureau of Justice Statistics (Justice Department)

Bureau of Labor Statistics (Labor Department)

Bureau of Transportation Statistics (Transportation Department)

Census Bureau (Commerce Department)

Economic Research Service (Agriculture Department)

Energy Information Administration (Energy Department)

National Agricultural Statistics Service (Agriculture Department) 

National Center for Education Statistics (Education Department)

National Center for Health Statistics (Health and Human Services Department) 

National Center for Science and Engineering Statistics (National Science Foundation)

Office of Research, Evaluation, and Statistics (Social Security Administration)

Statistics of Income Division (Treasury Department)

These agencies embrace a common set of professional standards and operational practices designed to 

ensure the quality, integrity and credibility of their statistical activities. Implementation of these 

professional standards involves a wide range of managerial and technical challenges. 

Principles and Practices of Statistical Agencies

To address these challenges, the National Research Council of the National Academies (NRC) has 

developed practical guidance in its publication, Principles and Practices for a Federal Statistical Agency2

. 

 1

The Office of Management and Budget designates principal statistical agencies. The exact number of units 

considered principal statistical agencies has evolved over time. The most recent listing of such agencies is available 

in the Office of Management and Budget’s Statistical Programs of the United States Government, available at: 

http://www.whitehouse.gov/sites/default/files/omb/assets/information_and_regulatory_affairs/12statprog.pdf.

2 National Research Council. Principles and Practices for a Federal Statistical Agency: Fourth Edition. Washington, 

DC: The National Academies Press, 2009. Available at: http://www.nap.edu/catalog.php?record_id=12564.
The principal statistical agencies use this volume to guide their strategic planning, daily operations, and 

interactions with stakeholders. The principal statistical agencies embrace the four fundamental 

principles articulated in the Fourth Edition: 

Principle 1: a Federal statistical agency must be in a position to provide objective information 

that is relevant to issues of public policy;

Principle 2: a Federal statistical agency must have credibility with those who use its data and 

information;

Principle 3: a Federal statistical agency must have the trust of those whose information it 

obtains; and

Principle 4: a Federal statistical agency must have a strong position of independence within the 

government.

Actual and perceived violations of any of these principles undermine the scientific integrity of, and 

public confidence in, the data produced by principal statistical agencies. Of special note is the emphasis 

that the NRC publication places on the impartiality and independence of each statistical agency. The 

NRC discussion of independence includes the following. 

- Independence must include separation of the statistical agency from the parts of its department

that are responsible for policy-making or law enforcement activities. 

- Independence must include control over personnel actions, especially the selection and 

appointment of qualified professional staff, including senior executive career staff.

- Independence must include the statistical agency having authority for professional decisions 

over the scope, content, and frequency of data collected; analysis, or publishing of the 

information; authority to release statistical information without prior clearance; and adherence 

to predetermined schedules for public release of statistical information. 

- Independence must also include the statistical agency’s ability to control information technology

systems used in collection, storage and dissemination of statistical information, since such 

control is essential for ensuring adherence to laws and regulations requiring appropriate 

protection of data collected under a promise of confidentiality. 

The principal statistical agencies also subscribe to the 11 practices identified by the NRC as critically

important in the application of these principles:

Practice 1: A Clearly Defined and Well-Accepted Mission; 

Practice 2: Continual Development of More Useful Data; 

Practice 3: Openness about Sources and Limitations of the Data Provided; 

Practice 4: Wide Dissemination of Data; 

Practice 5: Cooperation with Data Users;

Practice 6: Fair Treatment of Data Providers; 

Practice 7: Commitment to Quality and Professional Standards of Practice; 

Practice 8: An Active Research Program;

Practice 9: Professional Advancement of Staff; 

Practice 10: A Strong Internal and External Evaluation Program; and 

Practice 11: Coordination and Cooperation with Other Statistical Agencies. 

All of these practices are important to achieving and safeguarding scientific integrity. Implementation

details of these practices vary across agencies.
Statistical Policy Directives and Standards 

The Principles and Practices are closely related to Statistical Policy Directives and other standards issued 

by the Office of Management and Budget (OMB) in its role as coordinator of the Federal statistical 

system (44 U.S.C. 3504(e). Specifically, OMB’s directives and standards are designed to preserve and 

enhance the objectivity, utility, and transparency, in fact and in perception, of the statistical products 

themselves and the processes used to release and disseminate them. Examples include –

Statistical Policy Directive Number 33

, which is intended to preserve the time value of principal 

economic indicators, strike a balance between timeliness and accuracy, prevent early access to 

information that may affect financial and commodity markets, and preserve the distinction 

between the policy-neutral release of data by statistical agencies and their interpretation by 

policy officials. 

Statistical Policy Directive Number 44

, which enumerates procedures intended to ensure that 

statistical data releases adhere to data quality standards through equitable, policy-neutral, and 

timely release of information to the general public.

Standards and Guidelines for Statistical Surveys5

, which documents important technical and 

managerial practices that Federal agencies are required to adhere to, and the level of quality 

and effort expected in all statistical activities to ensure consistency among and within statistical 

activities conducted across the Federal Government. 

Information Quality Guidelines

The Principles and Practices are also related to the Information Quality Act6

, which requires OMB and

all other Federal agencies to maximize the quality, objectivity, utility, and integrity of information, 

including statistical information, provided to the public. Through the adoption and implementation of 

the Government-wide Information Quality Guidelines7

, each statistical agency–

maintains its commitment to using the best available science and statistical methods;

subjects information, models, and analytic results to independent peer review by qualified 

experts, when appropriate;

 3

http://www.whitehouse.gov/sites/default/files/omb/assets/omb/inforeg/statpolicy/dir_3_fr_09251985.pdf; 

38932 Federal Register / Vol. 50, No. 186 / Wednesday, September 25, 1985.

4

http://www.whitehouse.gov/sites/default/files/omb/assets/omb/fedreg/2008/030708_directive-4.pdf; 12622 

Federal Register / Vol. 73, No. 46 / Friday, March 7, 2008.

5 http://www.whitehouse.gov/sites/default/files/omb/assets/omb/inforeg/statpolicy/standards_stat_surveys.pdf; 

announced in 55522 Federal Register / Vol. 71, No. 184 / Friday September 22, 2006. 

6

Section 515 of the Treasury and General Government Appropriations Act, 2001 (Pub. L. No. 106-554, 44 U.S.C. § 

3516 note).

7

These guidelines are available at: http://www.whitehouse.gov/omb/fedreg/reproducible2.pdf.
disseminates its data and analytic products with a high degree of transparency about the data 

and methods to facilitate its reproducibility by qualified third parties; and 

ensures that the presentation of information is comprehensive, informative, and 

understandable. 

Using Best Scientific Methods to Ensure Data Quality and Integrity

Finally, scientific methods play a critical role in maximizing the quality, objectivity, and credibility of 

information collected and disseminated by the principal statistical agencies. Examples of the application 

of scientific methods include probability sampling designed to avoid biased samples and randomized 

assignment for assessing the impacts of alternative protocols or question wording. Measures need to be 

valid and reproducible, and interpreting variations in these measures across data sources requires 

scientific knowledge of their properties. Combining data from disparate sources, such as surveys and 

administrative records, is increasingly important given the growing reluctance of respondents to provide 

data in Federal data collection efforts. These efforts require statistical modeling, as does the provision of 

statistics on small areas where direct estimates from surveys may be subject to large sampling errors. 

The procedures, equations, and assumptions, which define these models, must be publicly available to 

ensure that the information is presented in an accurate, clear, complete, and unbiased manner. 

Moreover, Federal statistical agencies apply complex statistical methods to the information that is 

publicly released to protect the confidentiality of data about respondents to Federal surveys.

Methodological improvements and rigorous approaches to data collection and analysis require the 

application of scientific methods. Computer scientists, demographers, economists, geographers, 

mathematicians, survey statisticians, and other scientists are needed for producing high quality, 

objective statistics from surveys or administrative data. Subject area experts, such as epidemiologists 

and engineers, are also needed to maximize data quality. Research and methodological innovation are

required to continuously improve the quality and scope of our data products while protecting privacy 

and ensuring confidentiality. All of the above mentioned factors are critically important to ensuring the 

credibility of Federal statistical agencies. 

Conclusion

We reaffirm our commitment to maintaining the highest level of scientific integrity in producing official 

statistics. Together, the Principles and Practices, Statistical Policy Directives and Standards, and 

Information Quality Guidelines form the foundation for achieving and maintaining scientific integrity 

within and among the principal statistical agencies.