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Editing: Editing is a process that tries to ensure the accuracy, completeness, and consistency of survey data. Efforts are made at all phases of collection, processing, and tabulation to minimize reporting, keying, and processing errors.
Although some edits are built into the Internet data collection instrument and the data entry programs, the majority of the edits are performed post collection. Edits consist primarily of two types: (1) consistency edits and (2) a ratio edit.
The consistency edits check the logical relationships of data items reported on the form. For example, if a value exists for employees for a function then a value must exist for payroll also. If part-time employees and payroll exist then part-time hours must exist and vice versa.
For each function reported for the employees, the ratio edits compare data for the number of employees and the average salary between reporting years. If data fall outside of acceptable tolerance levels, the item is flagged for review.
For ratio edits and consistency edits, the edit results are reviewed by analysts and adjusted as needed. When the analyst is unable to resolve or accept the edit failure, contact is made with the respondent to verify or correct the reported data.
Imputation: Not all respondents answer every item on the questionnaire. There are also questionnaires that are not returned despite efforts to gain a response. Imputation is the process of filling in missing or invalid data with reasonable values in order to have a complete data set for estimating state and national totals.
For nonresponding general purpose governments, dependent and independent school districts, and for special district governments, the imputations were based on recent historical data from either a prior year annual survey or the 2007 Census of Governments: Employment Component, if available. These data were adjusted by a growth rate that was determined by the growth of responding units that were similar (in size, geography, and type of government) to the nonrespondent. If there were no recent historical data available, the imputations were based on the data from a randomly selected responding donor that was similar (based on the same criteria) to the nonrespondent. For general purpose governments, and for dependent and independent school districts, the selected donor's data were adjusted by dividing each data item by the population (or enrollment) of the donor and multiplying the result by the nonrespondent's population (or enrollment).
Because of the merging of dependent and independent schools in Maine, this state had to be imputed by itself. We also had to use a crosswalk so that the proper prior year data would be used for imputing the nonrespondents.
Note: Between years 2002 through 2006, individual government imputed data were not released to the public. Beginning with 2007, the imputed data are available on the Individual Government Data file. Data flags are available on the Individual Government Data file to denote the imputed data.
Tabulation:After the data were edited and imputed, the 2012 Census of Governments Employment data were aggregated to yield the viewable and downloadable files that are available on the Website. In the publications for employment statistics, full-time employees, full-time pay, part-time employees, part-time pay, full-time equivalent employment, and total March pay are published.
Sampling Variability: The data for the census are not subject to sampling and do not contain sampling error. The user should be mindful that the data for years not ending in 2 or 7 are from sample surveys and are subject to sampling error. Discussions of sampling error are available in the survey methodology descriptions for those years. For any comparisons of census year data to a sample year, the data user must perform hypothesis tests using the survey years sampling errors. For the census year, the sampling error is zero.