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6 Weighting and Estimation
Pages 71-94

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From page 71...
... The methodology is expected to evolve based on decisions made about revising other aspects of the survey design, particularly the imputation plans discussed later in this chapter. WEIGHTING PROCEDURES The ACS estimates are based on a raking ratio estimation procedure that results in two sets of weights: a weight assigned to each sample person record and a weight assigned to each sample housing unit record.
From page 72...
... PEP CONTROLS AND ALTERNATIVES The population controls used in the ACS weighting process are based on estimates produced by the Census Bureau's Population Estimates Program. The PEP publishes total population estimates annually, based on a methodol
From page 73...
... As the decade progresses, the census counts become increasingly outdated and the updates, such as the GQR data collected from states, cannot always be relied on, which affects the overall quality of the GQ population estimates. For some GQ types, the population estimates are basically the decennial census counts kept constant.
From page 74...
... TABLE 6-2 MAPE and MALPE of County-Level ACS Estimates of Group Quarters Compared with Expected GQ Counts ACS 0509/ ACS 0709/ ACS 09/ Region Expected 2007 Expected 2008 Expected 2009 Northeast MAPE 22.3 20.8 23.4 MALPE 5.2 7.4 9.9 Midwest MAPE 56.8 28.1 26.4 MALPE 17.1 13.1 7.8 West MAPE 64.8 27.2 26.0 MALPE 8.0 6.0 4.1 South MAPE 55.9 39.1 30.4 MALPE 14.9 19.3 9.4 Counties with population MAPE 86.2 118.0 -- under 20,000 MALPE 20.0 56.3 -- NOTES: Expected counts are interpolated based on the 2000 and 2010 census counts. ACS = American Community Survey, GQ = group quarters, MALPE = mean algebraic percent error, MAPE = mean absolute percent error.
From page 75...
... ACS = American Community Survey, GQ = group quarters, MALPE = mean algebraic percent error, MAPE = mean absolute percent error. SOURCE: Calculated by the panel based on 2000 census data and the 2010 census Advance Group Quarters Summary File.
From page 76...
... The Census Bureau awarded eight contracts to external researchers to evaluate the 2010 round of population estimates against the 2010 census and to assess alternative population estimation methodologies. The purpose of this work is to evaluate the current PEP method by comparing the population estimates of the total resident population and the household popu lation at the national, state, and county levels with the census counts.
From page 77...
... Recommendation 6-1: The Census Bureau should conduct an evaluation of the 2010 American Community Survey estimates of the group quarters (GQ) population against the 2010 census counts at all levels of geography for which the Census Bureau's Population Estimates Program (PEP)
From page 78...
... Finally, the Census Bureau should evaluate whether data from outside sources that are currently used to provide updates for the sampling frame could also be used for controls. ESTIMATES OF THE GQ POPULATION IN SMALL AREAS The decennial census, because of its role of providing complete counts of the population down to the census block level, mostly succeeds in completely enumerating the GQ population everywhere and is able to support counts by GQ type for all entities in the census geographic hierarchy.
From page 79...
... . TABLE 6-7 GQ Sample in Census Tracts with Group Quarters on the ACS Sampling Frame by Major Type of Group Quarters, 2006-2009 Percentage of Percentage of Total Number of Tracts with Tracts Without Tracts with GQ Major GQ Type ACS Sample ACS Sample Type on Frame Correctional facilities for adults 57.7 42.3 4,994 Juvenile facilities 40.2 59.8 2,818 Nursing facilities/skilled nursing facilities 59.4 40.6 16,583 Other institutional facilities 27.1 72.9 3,633 College/university student housing 72.5 27.5 3,351 Military group quarters 49.8 50.2 576 Other noninstitutional facilities 28.7 71.3 34,971 Total 47.9 52.1 66,926 SOURCE: U.S.
From page 80...
... For example, based on the census 2010 numbers, 19.2 percent of the county's total population is black, whereas the 5-year ACS estimates show the black population to be 30 percent. The source of the problem seems to be the disproportional weighting up of the prisons in Goochland County to account for the lack of sample cases of prisons in other areas in the state.
From page 81...
... It produces annual small-area income and poverty estimates for school districts, counties, and states using a model-based approach that relies on combining survey data with population estimates and administrative records (National Research Council, 2000)
From page 82...
... CENSUS BUREAU IMPUTATION PLANS TO IMPROVE THE GQ ESTIMATES In parallel with the panel's work on this study, the Census Bureau has been conducting its own internal research to identify ways of improving the ACS estimates for substate geographies. Its research is focused on the possibility of using data from in-sample GQ facilities to impute person records for group quarters that are not in sample but are either on the ACS sampling frame or known to exist based on information from the 2010 census (Erdman and Nagaraja, 2010)
From page 83...
... • For each small group quarters selected, person records equal to 20 percent of the population (expected based on the sampling frame) are imputed.
From page 84...
... The donor pool is set to the first combination of geography and GQ type in which there is at least one donor per five imputed records, from the list of combinations below: • County and specific type • County and major type • State and specific type • State and major type • Division and specific type • Division and major type • Region and specific type • Region and major type • Specific type without restriction • Major type without restriction Another option for donor selection is to apply a K-means clustering algo rithm that selects donors from tracts that are demographically similar. The Census Bureau identified eight demographic clusters of tracts as part of the marketing campaign for the 2010 census, taking into consideration tract characteristics, such as vacancy rates, housing unit type, family structure, poverty
From page 85...
... Evaluation of the Imputation Methodology The Census Bureau compared the imputation methods proposed and the current design-based ACS method using a GQ population simulated based on census 2000 data, using estimates of age, sex, race, and Hispanic origin for comparison (Erdman and Nagaraja, 2010)
From page 86...
... Larger differences were observed for "other long-term care" and "other noninstitutional" categories, which were also the GQ types with the higher imputation rates. Limitations of the Imputation Method The imputation methods are largely dependent on the quality of the sampling frame.
From page 87...
... of State of Donors Correctional facilities for adults FALSE 3.9 9.3 0.9 0.0 14.2 (132,931) TRUE 40.5 15.5 25.4 4.5 85.8 Juvenile facilities FALSE 1.7 13.8 17.7 1.9 35.1 (23,031)
From page 88...
... file and would be valuable to data users. By contrast, small-area estimation would involve con structing separate estimates for group quarters, which would then be combined with the household estimates to obtain total population estimates.
From page 89...
... TABLE 6-11 Item Imputation Rates (in percentage) for Selected Characteristics by GQ Type, 2005-2009 American Community Survey One or Speaks More Another Hispanic Income Marital Language Mobility Veteran Major GQ Type Sex Age Race Origin Source Status Citizenship at Home Status Status Total GQ population 0.2 1.1 2.5 3.1 37.9 5.0 5.7 10.7 7.7 10.2 Correctional facilities for adults 0.2 0.5 1.5 2.3 27.0 6.6 3.4 11.7 8.1 9.1 Juvenile facilities 0.3 3.2 2.0 2.8 25.4 3.0 5.4 10.0 7.8 7.7 Nursing facilities/skilled nursing facilities 0.2 1.2 0.7 1.6 63.4 3.3 6.0 9.5 5.6 13.1 Other institutional facilities 0.3 11.4 1.6 4.2 44.2 6.6 11.0 14.5 10.1 15.1 College/university student housing 0.1 0.8 5.4 5.4 28.8 5.8 7.6 12.4 9.2 10.5 Military group quarters 0.0 0.3 2.4 2.1 16.7 2.0 4.3 6.9 6.3 2.1 Other noninstitutional facilities 0.2 1.3 1.4 2.1 43.1 4.3 5.5 8.3 7.3 9.5 2005 household population 0.2 0.8 1.6 1.5 18.0 5.4 1.6 1.7 2.1 2.1 NOTE: The 2005 American Community Survey did not include group quarters.
From page 90...
... 90 TABLE 6-12 Item Imputation Rates (in percentage) for Selected Characteristics of the GQ Population by State, 2005-2009 American Community Survey One or Speaks More Another Hispanic Income Marital Language Mobility Veteran State Sex Age Race Origin Source Status Citizenship at Home Status Status Alabama 0.2 0.7 0.8 2.7 28.7 4.6 3.4 6.0 5.8 7.5 Alaska 0.2 0.5 1.2 0.8 11.1 2.7 3.3 3.7 3.4 3.6 Arizona 0.1 0.5 3.1 3.3 30.0 7.4 6.0 9.0 7.2 9.8 Arkansas 0.0 1.0 2.3 1.2 38.4 2.3 4.6 6.4 5.4 7.9 California 0.2 1.0 3.6 2.8 36.6 7.5 8.3 12.3 7.8 12.8 Colorado 0.0 0.4 2.0 2.3 44.1 3.7 4.2 22.1 17.9 23.4 Connecticut 0.1 0.6 4.2 4.1 48.1 4.8 8.9 13.3 10.3 9.0 Delaware 0.0 0.3 1.5 3.0 37.6 2.0 11.0 15.6 14.9 8.7 District of Columbia 0.1 2.6 3.5 3.9 48.2 10.0 12.8 20.3 20.7 27.8 Florida 0.3 1.0 2.0 3.7 32.9 5.6 7.3 11.3 9.1 12.0 Georgia 0.3 0.4 1.0 1.4 22.1 1.9 2.0 4.1 2.8 4.1 Hawaii 0.1 1.0 1.4 1.9 29.8 1.1 1.8 4.6 2.8 7.6 Idaho 0.1 0.6 0.3 0.5 18.5 0.3 1.1 5.1 1.6 3.1 Illinois 0.2 1.5 2.7 3.4 41.4 3.4 4.5 9.9 5.2 10.3 Indiana 0.3 1.4 1.0 1.7 44.4 5.7 7.6 14.0 11.6 15.7 Iowa 0.1 0.8 3.3 3.9 49.7 5.6 6.5 9.8 7.0 10.7 Kansas 0.2 0.5 3.8 4.2 45.2 4.5 5.0 10.0 7.3 10.1 Kentucky 0.1 0.6 1.3 1.7 34.5 2.4 3.8 6.8 5.2 7.9 Louisiana 0.1 1.6 0.5 2.4 34.5 3.1 2.2 6.7 6.8 8.2 Maine 0.0 0.3 4.9 6.4 41.3 11.9 13.3 19.2 13.0 18.1 Maryland 0.3 0.6 2.7 3.1 36.0 4.3 8.4 14.7 12.7 16.3 Massachusetts 0.1 0.9 4.2 4.7 50.8 9.3 13.6 19.8 12.4 16.9 Michigan 0.1 0.6 1.1 1.5 33.9 2.8 2.7 4.5 3.5 6.3 Minnesota 0.1 0.6 2.1 2.8 52.6 2.8 4.6 7.4 5.1 8.4 Mississippi 0.2 0.5 0.4 1.1 28.4 2.0 2.8 5.9 4.6 6.7
From page 91...
... Missouri 0.1 1.5 0.4 0.9 38.0 1.8 1.1 3.3 1.8 4.6 Montana 0.0 0.4 0.4 0.6 40.6 2.3 1.4 3.6 2.9 3.7 Nebraska 0.0 0.9 1.2 0.9 45.7 2.0 1.6 3.4 1.3 4.7 Nevada 0.2 0.5 1.3 0.6 23.4 1.7 1.5 3.1 1.7 2.3 New Hampshire 0.1 1.2 2.3 3.9 42.7 3.7 3.4 7.1 3.8 8.6 New Jersey 0.3 0.9 2.0 3.7 50.4 3.6 6.8 17.4 13.6 16.0 New Mexico 0.0 2.6 2.2 2.5 35.6 2.9 4.4 13.2 7.4 9.8 New York 0.3 2.5 6.1 6.7 42.8 7.6 9.4 15.4 10.0 12.8 North Carolina 0.1 0.8 1.4 2.1 34.7 4.1 3.5 7.8 5.7 9.0 North Dakota 0.0 0.1 0.6 0.3 41.7 0.8 1.7 3.2 2.3 3.6 Ohio 0.0 0.5 0.9 1.5 38.3 2.1 2.9 5.1 2.4 6.9 Oklahoma 0.1 1.1 2.9 3.5 36.2 3.8 2.5 7.0 5.0 7.3 Oregon 0.4 3.7 0.6 1.2 26.4 2.0 2.3 3.3 2.9 5.5 Pennsylvania 0.2 1.3 4.0 4.9 46.7 12.3 6.5 19.0 17.8 11.4 Rhode Island 0.0 0.3 5.9 9.9 37.0 10.5 11.9 13.3 12.3 14.1 South Carolina 0.1 0.2 1.1 3.0 31.2 2.4 4.8 7.8 6.9 10.0 South Dakota 0.0 1.4 0.7 0.7 34.7 0.7 0.9 2.2 2.0 2.3 Tennessee 0.0 1.0 1.3 1.9 36.3 4.0 5.2 9.8 9.0 11.3 Texas 0.2 1.2 1.3 2.0 29.2 3.0 3.7 5.8 4.9 6.8 Utah 0.1 1.7 1.2 1.2 27.1 1.5 5.1 8.6 6.9 4.1 Vermont 0.1 0.1 5.8 7.1 37.6 6.2 6.7 12.2 9.7 13.5 Virginia 0.2 0.7 2.1 2.7 44.0 4.5 4.9 19.8 5.5 8.3 Washington 0.1 1.2 1.3 2.1 33.8 5.7 6.2 8.2 6.4 9.4 West Virginia 0.0 1.0 3.0 4.5 44.8 4.6 4.8 11.1 9.6 13.2 Wisconsin 0.2 0.4 3.7 3.6 38.8 4.9 4.8 8.4 6.3 9.5 Wyoming 0.0 2.5 3.1 3.1 43.2 3.7 3.5 9.9 8.2 8.0 Puerto Rico 0.1 0.3 0.7 0.8 27.5 1.4 0.4 0.6 0.8 1.9 SOURCE: Beaghen (2011)
From page 92...
... Recommendation 6-4: The Census Bureau's research on imputing group quarters (GQ) person records in the American Community Survey should further investigate the possibility of using a donor selection procedure that deemphasizes geographic proximity in relation to matching by GQ type, trying out alternatives to the proposed sequence of collapsing the combinations of geography and GQ type.
From page 93...
... The Census Bureau should conduct an assessment of the reasons for the high item imputation rates and the need for revisions to the questionnaire, possibly conducting cognitive interviews with GQ residents living in different GQ types, and an analysis of the impacts of the revisions on both data quality and ability to meet data user needs. Customizing the questionnaire would reduce the burden on GQ respondents, which is likely to have a positive impact not only on the questions that have high imputation rates but also on other questions, which may be affected by cognitive shortcuts taken by respondents as a result of the less than optimal questionnaire design.
From page 94...
... 94 SMALL POPULATIONS, LARGE EFFECTS imputation rates, improving data quality, and reducing the burden on the GQ respondents who are required to answer questions that are not appli cable to their circumstances. Changes to consider should include omitting or revising some of the questions on the GQ questionnaire for some types of group quarters.


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