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Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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References

Alexander, C.H. (1993). A continuous measurement alternative for the U.S. census. Report CM-10, October 28. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

______ (1997). Impact of multiyear averaging of data from the American Community Survey. Pp. 644-649 in Proceedings of the Joint Statistical Meetings, ASA Section on Survey Research Methods. Alexandria, VA: American Statistical Association.

______ (1998, August). Recent developments in the American Community Survey. Paper prepared for the Joint Statistical Meetings, Dallas. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

______ (2001). Still rolling: Leslie Kish’s “rolling samples” and the American Community Survey. In Proceedings of Statistics Canada Symposium 2001—Achieving data quality in a statistical agency: A methodological perspective. Ottawa: Statistics Canada.

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Asiala, M.E. (2004). Specifications for selecting the ACS 2005 main HU sample (ACS-S-40). Draft memorandum to L. McGinn from R. Singh. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

______ (2005). American Community Survey research report: Differential sub-sampling in the computer assisted personal interview sample selection in areas of low cooperation rates. Memorandum to R. Singh from D. Hubble. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

______ (2007, February 21). ACS weighting and estimation research. PowerPoint presentation. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Bell, W.R. (2006). Using statistical models to combine CPS and ACS income and poverty estimates with other data (administrative records). Draft paper, May 8. Prepared for the Workshop Exploring Possible Development of One Set of Integrated Income and Poverty Estimates, May 30-31. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Biemer, P.P., and Lyberg, L.E. (2003). Introduction to survey quality. Hoboken, NJ: John Wiley and Sons, Inc.

Blumerman, L.M., and Simon, C.R. (2006). Subnational population estimates for the 1990s: An evaluation. Draft paper. Population Division, U.S. Bureau of the Census, U.S. Department of Commerce, Washington, DC.

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Bureau of Transportation Statistics (1996, April). Implications of continuous measurement for the uses of census data in transportation planning. Washington, DC: U.S. Department of Transportation.

Chakrabarty, R., assisted by G. Torres (1996). The American Housing Survey—A quality profile. Current Housing Reports, H121/95-1. Office of Policy Development and Research, U.S. Department of Housing and Urban Development and U.S. Census Bureau. Washington, DC: U.S. Department of Commerce.

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______ (1992). Using administrative record information to evaluate the quality of the income data collected in the Survey of Income and Program Participation. In Proceedings of Statistics Canada Symposium 92—Design and analysis of longitudinal surveys. Ottawa: Statistics Canada.

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Devine, J.E., and Coleman, C.D. (2003). People might move but housing units don’t: An evaluation of the state and county housing unit estimates. Population Division Working Paper Series No. 71. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

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Energy Information Administration (1996). Residential energy consumption survey quality profile. Prepared by T.B. Jabine. Washington, DC: U.S. Department of Energy.

Fay, R.E. (2005). Model-assisted estimation for the American Community Survey. Pp. 3016-3023 in Proceedings of the Joint Statistical Meetings, ASA Section on Survey Research Methods. Alexandria, VA: American Statistical Association.

Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

______ (2006). Using administrative records with model-assisted estimation for the American Community Survey. In Proceedings of the Joint Statistical Meetings. Alexandria, VA: American Statistical Association.

Groves, R., Fowler, F., Couper, M., Lepkowski, J., Singer, E., and Tourangeau, R. (2004). Survey methodology. Hoboken, NJ: John Wiley and Sons, Inc.

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Hefter, S.P. (2005a, June 16). Specifications for selecting the main and supplemental housing unit address samples for the American Community Survey. 2006 American Community Survey Sampling Memorandum Series #ACS06-S-3, draft memorandum to L. McGinn from R.P. Singh. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

______ (2005b, May 19). Specifications for selecting the American Community Survey group quarters sample. 2006 American Community Survey Sampling Memorandum Series #ACS06-S-6, draft memorandum to L. McGinn from R.P. Singh. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Horvitz, D.G. (1986, May 1). Statement to the Subcommittee on Census and Population, Committee on Post Office and Civil Service, U.S. House of Representatives. Research Triangle Park, NC: Research Triangle Institute.

Huang, E.T., and Bell, W.R. (2005). An empirical study on using ACS supplementary survey data in SAIPE state poverty models. Working paper. Statistical Research Division, U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Israel, S. (2006). Disability in the San Francisco Bay area: Comparing data between Census 2000 and the American Community Survey 2000-2004. Working paper. Planning Section, Metropolitan Transportation Commission, Oakland, CA.

Kalton, G., Levine, D.B., Waksberg, J., and Helmick, J. (1998, June 29). The American Community Survey—The quality of rural data: Report of a conference. Rockville, MD: Westat.

Kalton, G., Winglee, M., Krawchuk, S., and Levine, D. (2000). Quality profile for SASS rounds 1-3: 1098-1005: Aspects of the quality of data in the Schools and Staffing Surveys (SASS). Washington, DC: U.S. Department of Education, National Center for Education Statistics.

Kish, L. (1992). Weighting for unequal Pi. Journal of Official Statistics, 8, 183-200.

Kish, L., and Hess, I. (1959). A “replacement” procedure for reducing the bias of nonresponse. The American Statistician, 49, 520-538.

Maples, J.J. (2004, August). Investigating the use of IRS tax data in the SAIPE school district poverty estimates. Presentation to the Joint Statistical Meetings. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Martin, E., and Gerber, E. (2003, August 5). Methodological influences on comparability of race measurements: several cautionary examples. Paper prepared for the Joint Statistical Meetings, San Francisco. U.S. Bureau of the Census, U.S. Department of Commerce, Washington, DC.

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______ (2000a). Small-area estimates of school-age children in poverty—Evaluation of current methodology. Panel on Estimates of Poverty for Small Geographic Areas, C.F. Citro and G. Kalton, eds. Committee on National Statistics. Commission on Behavioral and Social Sciences and Education. Washington, DC: National Academy Press.

Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

______ (2000b). Small-area income and poverty estimates—Priorities for 2000 and beyond. Panel on Estimates of Poverty for Small Geographic Areas, C.F. Citro and G. Kalton, eds. Committee on National Statistics. Commission on Behavioral and Social Sciences and Education. Washington, DC: National Academy Press.

______ (2001). The 2000 census: Interim assessment. Panel to Review the 2000 Census, C.F. Citro, D.L. Cork, and J.L. Norwood, eds. Committee on National Statistics. Division of Behavioral and Social Sciences and Education. Washington, DC: National Academy Press.

______ (2003a). Statistical issues in allocating funds by formula. Panel on Formula Allocations, T.A. Louis, T.B. Jabine, and M.A. Gerstein, eds. Committee on National Statistics. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

______ (2003b). Survey automation: Report and workshop proceedings. Oversight Committee for the Workshop on Survey Automation, M.L. Cohen, D.L. Cork, R. Groves, and W. Kalsbeek, eds. Committee on National Statistics. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

______ (2004a). Reengineering the 2010 census: Risks and challenges. Panel on Research on Future Census Methods, D.L. Cork, M.L. Cohen, and B.F. King, eds. Committee on National Statistics. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

______ (2004b). The 2000 census: Counting under adversity. Panel to Review the 2000 Census, C.F. Citro, D.L. Cork, and J.L. Norwood, eds. Committee on National Statistics. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

______ (2005). Expanding access to research data: Reconciling risks and opportunities. Panel on Access to Research Data, Committee on National Statistics. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

______ (2006). Once, only once, and in the right place: Residence rules in the decennial census. Panel on Residence Rules in the Decennial Census, D.L. Cork and P.R. Voss, eds. Committee on National Statistics. Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

Nelson, C. (2006, May 30). What do we know about differences between CPS and ACS income and poverty estimates? Paper prepared for the Workshop Exploring Possible Development of One Set of Integrated Income and Poverty Estimates. U.S. Bureau of the Census, U.S. Department of Commerce, Washington, DC.

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ORC Macro (2002, September). The American Community Survey: Challenges and opportunities for HUD. Paper prepared under contract for the U.S. Department of Housing and Urban Development, Washington, DC.

Palumbo, T. (2005, May 11). Toward improving the quality of labor force data from the American Community Survey. PowerPoint presentation. U.S. Bureau of the Census, U.S. Department of Commerce, Washington, DC.

Posey, K.G., and Welniak, E. (1998, March). Income in the ACS: Comparisons to the 1990 census. Prepared for the American Community Survey (ACS) symposium held at the Bureau of the Census, Suitland, Maryland. Last revised: June 17, 1999. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Reese, A.J. (2007, February 21). A comparison of housing unit estimates to the American Community Survey Master Address File. PowerPoint presentation. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
×

Resnick, D., and Obenski, S. (2006). Methods and file acquisitions supporting the expanded use of administrative records. Paper prepared for the Joint Statistical Meetings, Seattle. U.S. Census Bureau, U.S. Department of Commerce.

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Starsinic, M. (2005). American Community Survey: Improving reliability for small area estimates. Pp. 3592-3599 in Proceedings of the Joint Statistical Meetings, ASA Section on Survey Research Methods. (CD-ROM). Alexandria, VA: American Statistical Association.

Stern, S., and Brault, M. (2005, January 28). Disability data from the American Community Survey: A brief examination of the effects of a question redesign in 2003. Working paper. Housing and Household Economic Statistics Division, U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Taeuber, C.M. (2006). American Community Survey data for community planning. Victoria, British Columbia, Canada: Trafford Publishing.

Turek, J., Denmead, G., and James, B. (2005). Poverty estimates in the ACS and other income surveys: What is the impact of methodology? Working paper. Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services.

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______ (2001, July). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 1: Demonstrating operational feasibility. Washington, DC: U.S. Department of Commerce.

______ (2002a). 2002 census of governments, government organization. Vol. 1, no. 1. Washington, DC: U.S. Department of Commerce.

______ (2002b, May). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 2: Demonstrating survey quality. Washington, DC: U.S. Department of Commerce.

______ (2003, December). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 3: Testing the use of voluntary methods. Washington, DC: U.S. Department of Commerce.

______ (2004a, May). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 4: Comparing general demographic and housing characteristics with census 2000. Washington, DC: U.S. Department of Commerce.

______ (2004b, May). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 5: Comparing economic characteristics with census 2000. Washington, DC: U.S. Department of Commerce.

______ (2004c, June). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 7: Comparing quality measures: Comparing the American Community Survey’s three-year averages and census 2000’s long form sample estimates. Washington, DC: U.S. Department of Commerce.

______ (2004d, June). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 8: Comparison of the ACS 3-year average and the census 2000 sample for a sample of counties and tracts. Washington, DC: U.S. Department of Commerce.

Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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______ (2004e, June). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 9: Comparing social characteristics with census 2000. Washington, DC: U.S. Department of Commerce.

______ (2004f, July). Meeting 21st century demographic data needs—Implementing the American Community Survey, Report 10: Comparing selected physical and financial housing characteristics with census 2000. Washington, DC: U.S. Department of Commerce.

______ (2005, December). Census 2000, public use microdata sample (PUMS), United States, technical documentation. Washington, DC: U.S. Department of Commerce.

______ (2006, May). Design and methodology—American Community Survey. Washington, DC: U.S. Department of Commerce. Available: http://www.census.gov/acs/www.

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Zaslavsky, A.M., and Schirm, A.L. (2002). Interactions between survey estimates and federal funding formulas. Journal of Official Statistics, 18(3), 371-391.

Zayatz, L.V. (2005, December 13). ACS base tables on workplace and means of transportation review. Memorandum for L. McGinn. U.S. Census Bureau, U.S. Department of Commerce, Washington, DC.

Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Page 264
Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Page 265
Suggested Citation:"References." National Research Council. 2007. Using the American Community Survey: Benefits and Challenges. Washington, DC: The National Academies Press. doi: 10.17226/11901.
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Page 266
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Using the American Community Survey: Benefits and Challenges Get This Book
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The American Community Survey (ACS) is a major new initiative from the U.S. Census Bureau designed to provide continuously updated information on the numbers and characteristics of the nation’s people and housing. It replaces the “long form” of the decennial census. Using the American Community Survey covers the basics of how the ACS design and operations differ from the long-form sample; using the ACS for such applications as formula allocation of federal and state funds, transportation planning, and public information; and challenges in working with ACS estimates that cover periods of 12, 36, or 60 months depending on the population size of an area.

This book also recommends priority areas for continued research and development by the U.S. Census Bureau to guide the evolution of the ACS, and provides detailed, comprehensive analysis and guidance for users in federal, state, and local government agencies, academia, and media.

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