In this phase, statistics are produced, examined in detail, and made ready for dissemination. The Analyze phase is comprised of five sub-processes:
- 6.1.Prepare draft outputs - In this sub-process, collected data are transformed into statistical outputs; additional measurements such as indices, trends, or seasonally adjusted series are produced; and quality characteristics are recorded.
- 6.2.Validate outputs - In this sub-process, statisticians validate the quality of the outputs produced, in accordance with a general quality framework and expectations. This sub-process also includes activities involved with the gathering of intelligence and the cumulative effect of building a body of knowledge about a specific statistical domain. This knowledge is then applied to the current data collection in the current environment, to identify any divergence from expectations and allow informed analyses. Validation activities can include:
- Checking for requisite population coverage and response rates;
- Comparing the statistics with previous cycles (if applicable);
- Comparing statistics against other relevant data (both internal and external);
- Investigating inconsistencies in the statistics;
- Performing macro editing; and
- Validating the statistics against expectations and domain intelligence.
- 6.3.Scrutinize and explain - In this sub-process, statisticians gain in-depth understanding of the outputs. They use that understanding to scrutinize and explain the statistics produced for this cycle by assessing how well the statistics reflect their initial expectations, viewing the statistics from all perspectives using different tools and media, and carrying out in-depth statistical analyses.
- 6.4.Apply disclosure control – This sub-process ensures that the data and metadata to be disseminated do not breach rules of confidentiality. This may include checking for primary and secondary disclosure, as well as applying data suppression or perturbation techniques.
- 6.5.Finalize outputs - This sub-process ensures the statistics and associated information are fit for their intended purpose and have achieved the required quality level, and are thus ready for use. It includes:
- Completing consistency checks;
- Determining the level of release and applying caveats;
- Collating supporting information, including interpretation, briefings, measures of uncertainty, and other necessary metadata;
- Producing the supporting internal documents;
- Conducting pre-release discussions with internal subject matter experts; and
- Approving the statistical content for release.
|Description||ADePT was developed to automate and standardize the production of analytical reports. ADePT uses micro-level data from various types of surveys, such as Household Budget Surveys, Demographic and Health Surveys and Labor Force surveys to produce rich sets of tables and graphs for a particular area of economic research.|
Boston College Department of Economics - Statistical Software Components
|Description||For Stata users: a large collection of freely accessible programs.|
Household Sample Surveys in Developing and Transition Countries
|Author(s)||United Nations, Department of Economic and Social Affairs|
|Description||The present publication presents the "state of the art" on several important aspects of conducting household surveys in developing and transition countries, including sample design, survey implementation, non-sampling errors, survey costs, and analysis of survey data. The main objective of this handbook is to assist national survey statisticians to design household surveys in an efficient and reliable manner, and to allow users to make greater use of survey generated data. The publication’s 25 chapters have been authored by leading experts in survey research methodology around the world.|
The Analysis of Household Surveys: A Microeconomic Approach to Development Policy
|Description||This book reviews the analysis of household survey data, including the construction of household surveys, the econometric tools that are the most useful for such analysis, and a range of problems in development policy for which the econometric analysis of household surveys is useful and informative. The author's approach remains close to the data, relying on transparent econometric and graphical techniques to present the data so that policy and academic debates are clearly informed.|