EDITING AND IMPUTATION FOR ECONOMIC SURVEY DATA bY Roderick
نویسندگان
چکیده
This series contains research reports, written by or in cooperation with staff members of the Statistical Research Division, whose content may be of interest to the general statistical research community. The views reflected in these reports are not necessarily those of the Census Bureau nor do they necessarily represent Census Bureau statistical policy or practice. ABSTRACT At the U.S. Bureau of the Census, data in economic surveys may occasionally be missing as a result of a company's failure to respond to a certain question, for example. In addition, values of other variables may require editing because they are clearly implausible. Implausible (outlying) values may arise as a result of the failure of the respondent to understand the survey question. used to illustrate the method.
منابع مشابه
Household Finance and Consumption Network
1. There is inconsistent practice and some uncertainty on the terms “editing” and “imputation”. In this document we will refer to data editing as the procedure used to correct or reconcile contradictory information, whereas imputation is the procedure used to deal with missing data. The glossary of the United Nations Statistical and Economic Commission for Europe (UNECE) states that data editin...
متن کاملComparison of GEIS and SPEER for Editing Economic Data
Two computer systems are currently available for editing continuous, economic data: Statistics Canada's General Edit and Imputation System (GEIS) and the Census Bureau's Structured Programs for Economic Editing and Referrals (SPEER). GEIS, the more general of the two systems, uses linear inequality edits and provides several imputation options. SPEER uses ratio edits which are a special case of...
متن کاملCorrelates of Data Quality in the Consumer Expenditure Quarterly Interview Survey
The Consumer Expenditure Quarterly Interview Survey (CEQ) is an ongoing panel survey which collects detailed expenditure information from a national sample of households. High data quality is essential to accurately reflect the spending habits of American consumers. This study examines CEQ data quality in terms of the editing required during the data processing phase. Editing methods include im...
متن کاملCombining administrative and survey data: potential benefits and impact on editing and imputation for a structural business survey
1. The new European Regulation on Structural Business Statistics (SBS) (March 2008) establishes that, in order to estimate information on the structure of National production systems, Member States (MS) can integrate data available in different information sources, including administrative data. Besides, due to budget restrictions, MS need to reduce statistical production costs while maintainin...
متن کامل5 Statistical Data Editing
Statistical Data Editing (SDE) is the process of checking data for errors and correcting them. Winkler (1999) defined it as the set of methods used to edit (i.e., clean up) and impute (fill in) missing or contradictory data. The result of SDE is data that can be used for analytic purposes. Editing literature goes back to the 1960s with the contributions of Nordbotten (1965), Pritzker, et al. (1...
متن کامل