1. Technical Issues Associated with the American Community Survey Lisa Neidert NPC Poverty/American Community Survey Workshop July 12 - 15, 2010

2. Statistical Notes  Reference purposes Do not need to use for presentation on Thursday Often ignored for overview talks Often ignored, unless required by reviewer  Statistical issues are not ACS-specific Census Bureau is more sensitive to statistical issues in 2008 than they were in 2000, 1990  Confidentiality  Standard errors/Margins of Error in ACS, but not census products  Resources: http://www.psc.isr.umich.edu/dis/acs/handouts/Compass_Appendix.pdf http://www.psc.isr.umich.edu/dis/acs/dataanalysis/UsingReplicateWeights.html

3. Technical Appendices  Each Compass guide has the same glossary and set of appendices  http://www.psc.isr.umich.edu/dis/acs/han douts/Compass_Appendix.pdf http://www.psc.isr.umich.edu/dis/acs/han douts/Compass_Appendix.pdf

5. Big Picture  Appendix 3 – Definitions Standard Errors  How to get a SE from MOE Margin of Error  Reported with summary tabulations  How to change from 90% to 95%; 99% Confidence Interval Coefficient of Variation  Recommendations

6. Coefficient of Variation  CV = Standard Error/Population Estimate Note: Need to recover SE (Appendix 3)  The smaller the CV the more reliable the estimate is  Preferable that CV < 10%  If using a proportion, the closer the proportion is to 0, the more unstable the CV is

7. Coefficient of Variation...  1-year estimate vs 3-year estimate CV will be 70% larger for the 1-year estimate  Decision is precision vs currency  Use multi-year estimate if single year has CV > 10%  If single year CV is > 50 percent, do not use

8. Minimum population thresholds  Rule of thumb: Population estimate (weighted) should be:  >3,000 for 1-year  >1,000 for 3-year  >600 for 5-year  [From older draft of Appendix 6]  http://www.psc.isr.umich.edu/dis/workshop/npc2010/PDF/OldAppendix. pdf http://www.psc.isr.umich.edu/dis/workshop/npc2010/PDF/OldAppendix. pdf

9. Multiyear Estimates  When comparing multiyear estimates, use non-overlapping estimates 2005-2007 vs 2008-2010  Do not compare a single year estimate against a multiyear estimate Both should be multiyear estimates The single year estimate could be at the peak or trough of an economic cycle vs the more moderated multiyear estimate

10. Margins of Error for Derived Estimates  Summary data provide a margin of error for every cell  Researchers often combine cells Geography like NYC community districts comprised of multiple census tracts Cells within a geography  Combine several age groups

11. Spreadsheet  Illustrate New Derived MOE  http://www.psc.isr.umich.edu/dis/workshop/npc2010/PDF/Combined_MoE.xls http://www.psc.isr.umich.edu/dis/workshop/npc2010/PDF/Combined_MoE.xls

12. Statistical Significance  Appendix 4 ACS vs ACS ACS vs Census

13. Replicate Weights  To correct for the fact that the samples are not random  Census Bureau’s replicate weights are not handled by statistical packages (as an option, like JK or BRR)  SAS program that has the algorithm https://ctools.umich.edu/access/content/gr oup/34a72eab-daa4-4d14-80e0- 9150727aed6c/Technical%20- %20Statistical/sas_code_example.txt https://ctools.umich.edu/access/content/gr oup/34a72eab-daa4-4d14-80e0- 9150727aed6c/Technical%20- %20Statistical/sas_code_example.txt

14. Census Bureau recommendations for replicate weights  Garrett, B. Dale and Michael Starsinic. 2008. “ACS Public Use Microdata Samples of 2005 and 2006 – How to Use Replicate Weights.” Presentation at AAPOR Conference, New Orleans, May 16, 2008.  https://ctools.umich.edu/access/content/group/3 4a72eab-daa4-4d14-80e0- 9150727aed6c/Technical%20- %20Statistical/How%20to%20Use%20PUMS% 20Replicate%20Weights.ppt https://ctools.umich.edu/access/content/group/3 4a72eab-daa4-4d14-80e0- 9150727aed6c/Technical%20- %20Statistical/How%20to%20Use%20PUMS% 20Replicate%20Weights.ppt

15. Theoretical Basis for Successive Difference Model  Fay, R. and Train, G. 1995. “Aspects of Survey and Model-Based Postcensal Estimation of Income and Poverty Characteristics for States and Counties,” Proceedings of the Section on Governmental Statistics, American Statistical Association, pp. 154-159.