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The 2000 Census: Counting Under Adversity (2004)
Committee on National Statistics (CNSTAT)

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. "6 The 2000 Coverage Evaluation Program." The 2000 Census: Counting Under Adversity. Washington, DC: The National Academies Press, 2004.

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The 2000 Census: Counting Under Adversity

were geocoded to the wrong block, rising to as much as 11 percent of housing units in multiunit structures with 10 or more units (Vitrano et al., 2003b:76–77; see also Section 4-E.2). Hence, the usefulness of block statistics is not the data themselves, but the facility they provide for the user to aggregate the data to larger areas defined by the user (e.g., congressional districts, local service areas). Because geocoding errors typically involve nearby areas, the data for aggregates of blocks will be more accurate than the data for individual blocks.

6–D.5 Coverage Error in 2000, Group Quarters

We can say virtually nothing about coverage error for group quarters residents—either erroneous enumerations or omissions. Net undercount estimates for residents of noninstitutional group quarters from the 1990 PES were based on very uncertain data because of the difficulty of tracking such populations as college students on spring or summer break. Net undercount estimates for group quarters residents were not available from the A.C.E., which did not include this population in its universe. All indications are that the group quarters enumeration process was poorly controlled (see Section 4-F), so that coverage errors for group quarters residents were probably large.

6–D.6 Gross Coverage Errors

Although coverage correction factors for adjustment are based on estimated net error rates, components of gross error—that is, types of census omissions and erroneous enumerations—are important to measure and analyze to understand the census process and how to improve it. In this regard, higher or lower net undercount does not relate directly to the level of gross errors. There can be a zero net undercount and high rates of gross omissions and gross erroneous enumerations.

However, there is not widespread acceptance of the definition of different types of gross errors (see Section 1-C.1). Moreover, some types of gross errors depend on the level of aggregation or are not clearly identified by type in the design used for the A.C.E. and PES. Many errors identified by the A.C.E. or PES involved the balancing of

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