1. Sample Design on Historical Census Projects at the University of Minnesota Ron Goeken

2. Completed historical samples Census YearTarget PopulationSample DensityNumber of Person Records 1850U.S. Free Population1-in-100198,000 1860U.S. Free Population1-in-100274,000 1870U. S. Population1-in-100383,000 1880U. S. Population1-in-100503,000 1900U. S. Population1-in-100755,000 1910U. S. Population1-in-100917,000 1920U. S. Population1-in-1001,050,000

4. Sample design issues Goal is to sample entire households (or dwellings) Every individual has an equal probability of being sampled Practicality

5. Basic sample design Every household is defined as a cluster Samples are also stratified Only include in sample if the first person in a household is on a sample line. Probability of selection = np(1/n) = p 3 person household: 3*.01(1/3) =.01 8 person household: 8*.01(1/8) =.01

6. Group Quarters Not practical to sample large institutions in their entirety A better approach is to apply individual level sampling when household size exceeds a predetermined threshold.

7. Sampling rules – dwellings/households 1. If the dwelling contains 30 or fewer residents: –a) accept the entire dwelling if the sample point falls on the first listed individual in the dwelling. –b) reject the entire dwelling if the sample point falls on any other dwelling resident. 2. If the dwelling contains 31 or more residents and the household contains 30 or fewer persons: –a) accept the entire household if the sample point falls on the household head. –b) reject the entire household if the sample point falls on any other household member.

8. Sampling rules – group quarters 3. If the household contains 31 or more persons : –accept individuals on sample lines.

9. Target and Actual Sample Densities for Completed Historical Samples Census YearNumber of Person Records Target Sample Density Actual Sample Density 1850198,0001 %0.989 % 1860274,0001 %0.997 % 1870383,0001 %0.998 % 1880503,0001 %1.003 % 1900755,0001 %0.993 % 1910917,0001 %0.994 % 19201,050,0001 %0.992 %

10. Sample Confidence Interval Estimating the number of sample clusters in the total population # of sampled person records = # of sample clusters Total Population Total # of clusters

11. Source of under-sampling Some enumerator manuscripts were never microfilmed Data entry error Processing procedures can lead to deleting records, but rarely adding records Ambiguity on enumerator manuscripts

13. Percent of Target Records by Size of Place and Census Year Population category188019001920 100K+99.098.998.7 50K – 9999997.396.3100.4 25K – 49999100.597.899.0 10K – 24999101.498.697.5 5K – 999993.7100.199.6 2.5K – 499997.699.3 Under 2.5K100.098.799.6

14. Assigning Weights Each sampled individual represents X number of individuals in the total population. We have typically assigned weights at the national level.

15. County Level or SEA Level Weights 1. Weight at the county level if county population exceeds 10,000 and: –A. all other counties in the SEA have populations exceeding 10,000, or –B. the combined populations of the counties with populations under 10,000 is 10,000 or more. 2. If conditions above are not true, then weight at the SEA level.

16. Conclusion Sample designs are fairly straightforward in theory, but source materials and procedures result in under-sampling bias Detailed weights based on county populations or SEA populations theoretically improve precision