Table 3–1. Estimated <strong>Population</strong> in Sample Areas for 824-PSU <strong>Design</strong> by State State Self-representing (SR) areas <strong>Population</strong> 1 in SR areas Percentage Non-self-representing (NSR) areas <strong>Population</strong> 1 in NSR sample areas Percentage Total sample areas <strong>Population</strong> 1 in sample areas Percentage Total. . . .............. 161,282,405 76.1 18,957,760 8.9 180,240,165 85.0 Alabama ..................... 1,556,994 46.2 746,019 22.1 2,303,013 68.3 Alaska ....................... 336,349 77.2 28,541 6.5 364,890 83.7 Arizona ...................... 3,076,477 80.5 421,667 11.0 3,498,144 91.5 Arkansas ..................... 876,805 43.4 388,413 19.2 1,265,218 62.6 California . . . .................. 23,690,332 94.6 587,004 2.3 24,277,336 96.9 Los Angeles .............. 7,040,665 100.0 0 0.0 7,040,665 100.0 Remainder of California .... 16,649,667 92.5 587,004 3.3 17,236,671 95.8 Colorado ..................... 2,444,539 75.4 401,785 12.4 2,846,324 87.8 Connecticut. . ................. 2,588,699 100.0 0 0.0 2,588,699 100.0 Delaware ..................... 595,030 100.0 0 0.0 595,030 100.0 District of Columbia. . . ......... 457,495 100.0 0 0.0 457,495 100.0 Florida . ...................... 11,247,999 90.5 702,456 5.7 11,950,455 96.1 Georgia ...................... 3,921,187 64.7 730,347 12.1 4,651,534 76.8 Hawaii ....................... 902,559 100.0 0 0.0 902,559 100.0 Idaho ........................ 582,187 61.5 128,137 13.5 710,324 75.0 Illinois. . ...................... 7,459,357 79.9 875,368 9.4 8,334,725 89.3 Indiana....................... 2,504,432 54.6 705,866 15.4 3,210,298 69.9 Iowa . . . ...................... 718,299 32.2 590,359 26.5 1,308,658 58.7 Kansas....................... 1,028,154 51.5 294,193 14.7 1,322,347 66.2 Kentucky ..................... 1,414,196 45.9 525,654 17.1 1,939,850 63.0 Louisiana. . ................... 1,779,331 54.1 570,528 17.4 2,349,859 71.5 Maine . . . ..................... 831,273 83.7 104,708 10.5 935,981 94.2 Maryl<strong>and</strong> . . . .................. 3,635,366 91.2 249,759 6.3 3,885,125 97.5 Massachusetts ................ 4,915,261 100.0 0 0.0 4,915,261 100.0 Michigan ..................... 5,708,265 76.1 788,772 10.5 6,497,037 86.6 Minnesota . . .................. 2,534,229 68.2 293,420 7.9 2,827,649 76.1 Mississippi.................... 658,381 31.4 518,634 24.8 1,177,015 56.2 Missouri . . .................... 2,592,889 61.3 532,452 12.6 3,125,341 73.9 Montana . . ................... 449,818 65.6 60,735 8.9 510,553 74.4 Nebraska..................... 669,967 52.3 166,160 13.0 836,127 65.2 Nevada ...................... 1,361,183 90.3 73,785 4.9 1,434,968 95.2 New Hampshire . . ............. 946,316 100.0 0 0.0 946,316 100.0 New Jersey................... 6,424,830 100.0 0 0.0 6,424,830 100.0 New Mexico .................. 869,341 64.9 195,258 14.6 1,064,599 79.4 NewYork..................... 12,976,943 89.4 604,945 4.2 13,581,888 93.6 New York City............. 6,197,673 100.0 0 0.0 6,197,673 100.0 Remainder of New York .... 6,779,270 81.5 604,945 7.3 7,384,215 88.8 North Carolina ................ 3,227,560 53.0 1,112,224 18.2 4,339,784 71.2 North Dakota ................. 258,088 53.2 97,567 20.1 355,655 73.3 Ohio . . . ...................... 6,512,613 75.7 597,297 6.9 7,109,910 82.6 Oklahoma .................... 1,453,949 56.4 288,633 11.2 1,742,582 67.6 Oregon. ...................... 1,803,289 68.5 255,641 9.7 2,058,930 78.2 Pennsylvania . . ............... 7,456,685 78.7 877,672 9.3 8,334,357 88.0 Rhode Isl<strong>and</strong> . . ............... 810,041 100.0 0 0.0 810,041 100.0 South Carolina . ............... 1,923,917 63.7 330,931 11.0 2,254,848 74.7 South Dakota . ................ 320,381 57.2 105,941 18.9 426,322 76.1 Tennessee.................... 2,449,113 56.4 761,816 17.5 3,210,929 73.9 Texas . . ...................... 11,598,894 76.6 947,146 6.3 12,546,040 82.9 Utah . . . ...................... 1,228,567 78.1 157,145 10.0 1,385,712 88.0 Vermont. ..................... 472,874 100.0 0 0.0 472,874 100.0 Virginia....................... 3,750,284 70.9 460.699 8.7 4,210,983 79.6 Washington. . ................. 3,226,608 72.5 505,437 11.4 3,732,045 83.9 West Virginia ................. 778,715 54.5 256,355 17.9 1,035,070 72.4 Wisconsin .................... 2,021,672 49.6 877,326 21.5 2,898,998 71.1 Wyoming ..................... 234,672 63.3 40,965 11.0 275,637 74.3 1 Civilian noninstitutionalized population 16 years of age <strong>and</strong> over based on <strong>Census</strong> 2000. <strong>Current</strong> <strong>Population</strong> <strong>Survey</strong> TP66 U.S. <strong>Bureau</strong> of Labor Statistics <strong>and</strong> U.S. <strong>Census</strong> <strong>Bureau</strong> <strong>Design</strong> of the <strong>Current</strong> <strong>Population</strong> <strong>Survey</strong> Sample 3–5
Calculation of overall state sampling interval. After stratifying the PSUs within the states, the overall sampling interval in each state is computed. The overall state sampling interval is the inverse of the probability of selection of each housing unit in a state for a self-weighting design. By design, the overall state sampling interval is fixed, but the state sample size is not fixed, allowing growth of the CPS sample because of housing units built after <strong>Census</strong> 2000. (See Appendix B for details on how the desired sample size is maintained.) The state sampling interval is designed to meet the requirements for the variance on an estimate of the unemployment level. This variance can be thought of as a sum of variances from the first stage <strong>and</strong> the second stage of sample selection. 5 The first-stage variance is called the between-PSU variance <strong>and</strong> the second-stage variance is called the within-PSU variance. The square of the state CV, or the relative variance, on the unemployment level is expressed as where 2 σb 2 σw CV2 = σ 2 b 2 +σw [E(x)] 2 (3.1) = between-PSU variance contribution to the variance of the state unemployment level estimator. = within-PSU variance contribution to the variance of the state unemployment level estimator. E(x) = the expected value of the unemployment level for the state. 2 The term, σw, can be written as the variance assuming a binomial distribution from a simple r<strong>and</strong>om sample multiplied by a design effect where 2 σw= N2 pq(deff) n N = the civilian noninstitutionalized population, 16 years of age <strong>and</strong> older (CNP16+), for the state. p = proportion of unemployed in the CNP16+ for the state, or x N . n = the state sample size. deff = the state within-PSU design effect. This is a factor accounting for the difference between the variance calculated from a multistage stratified sample <strong>and</strong> that from a simple r<strong>and</strong>om sample. 5 The variance of an estimator, u, based on a two-stage sample has the general form: Var�u� � VarIEII�u� set of sample PSUs� � EIVarII�u� set of sample PSUs� where I <strong>and</strong> II represent the first <strong>and</strong> second stage designs, respectively. The left term represents the between-PSU variance, 2 2 σb. The right term represents the within-PSU variance, σw. Substituting. q=1–p. This formula can be rewritten as where 2 σw= SI (x q)(deff) (3.2) SI = the state sampling interval, or N n . Substituting (3.2) into (3.1) <strong>and</strong> rewriting in terms of the state sampling interval gives SI = CV2x2 2 −σb xq(deff) Generally, this overall state sampling interval is used for all strata in a state yielding a self-weighting state design. (In some states, the sampling interval is adjusted in certain strata to equalize field representative workloads.) When computing the sampling interval for the current CPS sample, a 6 percent state unemployment rate is assumed for 2005. Table 3-1 provides information on the proportion of the population in sample areas for each state. The SCHIP sample is allocated among the states after the CPS sample is allocated. A sampling interval accounting for both the CPS <strong>and</strong> SCHIP samples can be computed as: SI COMB � �SI CPS �1 �1 � SISCHIP� �1 The between-PSU variance component for the combined sample in the three states which were restratified for SCHIP can be estimated using a weighted average of the individual CPS <strong>and</strong> SCHIP between-PSU variance. The weight is the proportion of the total state sample accounted for by each individual survey: 2 �B,COMB 2 2 � (SICOMB�SICPS)�B,CPS � (1 � SICOMB�SICPS)�B,SCHIP SECOND STAGE OF THE SAMPLE DESIGN The second stage of the CPS sample design is the selection of sample housing units within PSUs. The objectives of within-PSU sampling are to: 1. Select a probability sample that is representative of the civilian noninstitutionalized population. 2. Give each housing unit in the population one <strong>and</strong> only one chance of selection, with virtually all housing units in a state or substate area having the same overall chance of selection. 3. For the sample size used, keep the within-PSU variance on labor force statistics (in particular, unemployment) at as low a level as possible, subject to respondent burden, cost, <strong>and</strong> other constraints. 4. Select within-PSU sample units for additional samples that will be needed before the next decennial census. 3–6 <strong>Design</strong> of the <strong>Current</strong> <strong>Population</strong> <strong>Survey</strong> Sample <strong>Current</strong> <strong>Population</strong> <strong>Survey</strong> TP66 U.S. <strong>Bureau</strong> of Labor Statistics <strong>and</strong> U.S. <strong>Census</strong> <strong>Bureau</strong>
- Page 1 and 2: Design and Methodology Current Popu
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- Page 7 and 8: CONTENTS Chapter 9. Data Preparatio
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still be associated with the state-
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Weights After National Coverage Adj
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Table 10−4: Second-Stage Adjustme
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Iteration 2: (Repeat steps above be
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1. For each state 7 and the Distric
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Production of monthly, quarterly, a
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for national CPS labor force series
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Chapter 11. Current Population Surv
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Table 11-1. Current Population Surv
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have completed their eighth and fin
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Table 11−3. Summary of 2004 ASEC
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Current Population Survey TP66 U.S.
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Chapter 12. Data Products From the
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Table 12-1. Bureau of Labor Statist
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Chapter 13. Overview of Data Qualit
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For example, we now recognize that
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the other panel in the SR SECU or N
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means that the estimates of varianc
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Table 14-2. Components of Variance
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Table 14-4. Effect of Compositing o
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Wolter, K. (1984), ‘‘An Investi
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• Master Address File (MAF): The
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no RO review of group quarters list
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5. The questionnaire does not elici
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chance to answer; probing technique
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Chapter 16. Quality Indicators of N
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Figure 16−2. Average Yearly Type
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Table 16-3. Labor Force Status by I
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supposed to be done in person, the
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Figure 16−4. Basic CPS Household
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Appendix A Sample Preparation Mater
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Illustration 1. Segment Folder, BC-
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Illustration 3. Unit/Permit Listing
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Illustration 5. Unit/Permit Listing
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Illustration 7. Permit Sketch Map,
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group numbers are chosen for deleti
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demographic components often cited
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2. The CPS control universe exclude
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A concern exists relative to the co
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The resulting race categories (Whit
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treat race and Hispanic origin as a
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REFERENCES Ahmed, B. and J. G. Robi
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Figure D-1. Map D-2 Organization an
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This report provides the supervisor
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Appendix E. Reinterview: Design and
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Acronyms ADS Annual Demographic Sup
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Births—Con. total population C-4
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Estimates, population—Con. popula
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Listing checks 15-4 Listing Sheets
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Ratio adjustments—Con. second-sta
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Vacancy rates 11-2, 11-4 Variance e