Research and Plans for Coverage Measurement in the 2010 Census Interim Assessment (2007) / Chapter Skim
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2 Back to Basics: What Are Census Errors and How Can They Be Measured?
2 Back to Basics: What Are Census Errors and How Can They Be Measured?
Pages 19-31
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From page 19... ...
First, erroneous enumerations are those who should not have been included in the census because they were not residents of the United States on Census Day, such as babies born after Census Day, people who died before Census Day, temporary visitors, and fabricated people. Second, there are duplicates of correct enumerations, representing people who appear more than once in the list of census enumerations.
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From page 20... ...
Omissions can result from a missed address on the MAF, a missed housing unit in a multiunit residence in which other residences were enumerated, a missed individual in a household with other enumerated people, and people with no residence. In addition to omissions, erroneous enumerations, and duplications, enumerations in the wrong location can also affect the accuracy of census counts.
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From page 21... ...
Furthermore, since component coverage errors have partially distinct causes, it is important to separate the summaries of these various components so that their magnitudes can be assessed individually, rather than trying to place them into a single error measure. These last two points argue for separate measures of the four components of census coverage error: duplicates, erroneous enumerations, omissions, and enumerations in the wrong location.
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From page 22... ...
users find net error measures useful for evaluating the utility of estimates for some applications. HOW CENSUS ERRORS ARE MEASURED In this section we provide some additional detail concerning the two main approaches to coverage measurement that were outlined in Chapter 1: DSE and demographic analysis.
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From page 23... ...
The independence of the P-sample enumerations and the census enumerations is crucial to support the estimation of census undercoverage for the following reason. The fundamental relationship underlying this approach to the estimation of census net undercoverage is that, poststratum by poststratum, the following approximate equation should obtain: M C ≅ P DSE where: • M stands for the estimate of the number of P-sample persons who match with an E-sample person, • P stands for the estimate of the number of all valid P-sample persons, • C stands for the number of census enumerations, and • DSE stands for the dual-systems estimate of the total number of residents, that is, the estimated true count.
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From page 24... ...
The assumption is that their net coverage error is the same as that for the remaining census enumerations. The number of CE matchable persons, C − II , is multiplied by to estimate the percentage of matchable E persons that are correct enumerations, that is, we multiply the matchable count by the percentage of correct census enumerations.
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From page 25... ...
This assumption can be examined using studies like the Evaluation Follow-Up Study in 2000. For duplicates, data-defined enumerations with name and date of birth in the E-sample within the P-sample block clusters are typically discovered, but until 2010, those duplicates outside the P-sample blocks were categorized as erroneous enumerations.
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From page 26... ...
restricted search area results in a substantial increase in the estimated rates of omission and erroneous enumeration, much of which is due to counting someone in the wrong location, which may not be an error for many applications of census data. Finally, errors in geography or demographics can also result in the placement of individuals in the wrong poststratum, which can also bias the estimation of net coverage error.
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From page 27... ...
Having pointed out some of the deficiencies of demographic analysis, it is important to emphasize its continuing value in coverage measurement. Demographic analysis places the census results within the well-defined, consistent, and essentially tautological framework of demographic change.
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From page 28... ...
Thus, if current research suggests that the demographic analysis coverage measures for a specific age group need to be adjusted (because, for example, the Medicare data show more or fewer enrollees than expected, or the births for a historical time period appear to be too high, or immigration during a decade had to have been higher or lower) , the adjustment affects the size of the age group not only in the current census but also in past ones as well.
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From page 29... ...
Consequently, a valuable use of coverage measurement is to help to identify sources of census coverage errors and to suggest alternative processes to reduce the frequency of those errors. Although drawing a link between census coverage errors and deficient census processes is a challenging task, the Census Bureau thinks that substantial progress can be made in this direction, since its objective going into the 2010 census is to use, to the extent feasible, the 2010 coverage measurement programs to help indicate the sources of common errors in the census counts.
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From page 30... ...
Here the process in need of modification is clear. On the other hand, a housing unit might be placed in the wrong location for many reasons, including an incorrect address in the MAF, a geocoding error using the TIGER geographic database, or an incorrect address entered by the respondent on a Be Counted form.5 The extent to which coverage measurement programs can specifically discriminate between different sources of census errors depends on the situation.
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From page 31... ...
A decision whether to use adjusted counts for any purpose must therefore rest on an assessment of the relative accuracy of the adjusted counts compared with the census counts at the relevant level of geographic and/or demographic aggregation. The Census Bureau's decision not to adjust the redistricting data, due for release by April 1, 2011, was based on the difficulty of making this assessment within the required time frame.
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