The SURVEYMEANS Procedure
Example 88.2 Domain Analysis
Suppose that you are studying profiles of 800 top-performing companies to provide information about their impact on the economy. You are also interested in the company profiles within each market type. A sample of 66 companies is selected with unequal probability across market types. However, market type is not included in the sample design. Thus, the number of companies within each market type is a random variable in your sample. To obtain statistics within each market type, you should use domain analysis. The data of the 66 companies are saved in the following data set:
data Company; length Type $14; input Type$ Asset Sale Value Profit Employee Weight; datalines; Other 2764.0 1828.0 1850.3 144.0 18.7 9.6 Energy 13246.2 4633.5 4387.7 462.9 24.3 42.6 Finance 3597.7 377.8 93.0 14.0 1.1 12.2 Transportation 6646.1 6414.2 2377.5 348.2 47.1 21.8 HiTech 1068.4 1689.8 1430.2 72.9 4.6 4.3 Manufacturing 1125.0 1719.4 1057.5 98.1 20.4 4.5 Other 1459.0 1241.4 452.7 24.5 20.1 5.5 Finance 2672.3 262.5 296.2 23.1 2.2 9.3 Finance 311.0 566.2 932.0 52.8 2.7 1.9 Energy 1148.6 1014.6 485.1 60.6 4.0 4.5 Finance 5327.0 572.4 372.9 25.2 4.2 17.7 Energy 1602.7 678.4 653.0 75.6 2.8 6.0 Energy 5808.8 1288.4 2007.0 318.8 5.9 19.2 Medical 268.8 204.4 820.9 45.6 3.7 1.8 Transportation 5222.6 2627.8 1910.0 245.6 22.8 17.4 Other 872.7 1419.4 939.3 69.7 12.2 3.7 Retail 4461.7 8946.8 4662.7 289.0 132.1 15.0 HiTech 6719.2 6942.0 8240.2 381.3 85.8 22.1 Retail 833.4 1538.8 1090.3 64.9 15.4 3.5 Finance 415.9 167.3 1126.8 56.8 0.7 2.2 HiTech 442.4 1139.9 1039.9 57.6 22.7 2.3 Other 801.5 1157.0 664.2 56.9 15.5 3.4 Finance 4954.8 468.8 366.4 41.7 3.0 16.5 Finance 2661.9 257.9 181.1 21.2 2.1 9.3 Finance 5345.8 530.1 337.4 36.4 4.3 17.8 Energy 3334.3 1644.7 1407.8 157.6 6.4 11.4 Manufacturing 1826.6 2671.7 483.2 71.3 25.3 6.7 Retail 618.8 2354.7 767.7 58.6 19.0 2.9 Retail 1529.1 6534.0 826.3 58.3 65.8 5.7 Manufacturing 4458.4 4824.5 3132.1 28.9 67.0 15.0 HiTech 5831.7 6611.1 9464.7 459.6 86.7 19.3 Medical 6468.3 4199.2 3170.4 270.1 59.5 21.3 Energy 1720.7 473.1 811.1 86.6 1.6 6.3 Energy 1679.7 1379.9 721.1 91.8 4.5 6.2 Retail 4018.2 16823.4 2038.3 178.1 162.0 13.6 Other 227.1 575.8 1083.8 62.6 1.9 1.6 Finance 3872.8 362.0 209.3 27.6 2.4 13.1 Retail 3359.3 4844.7 2651.4 224.1 75.6 11.5 Energy 1295.6 356.9 180.8 162.3 0.6 5.0 Energy 1658.0 626.6 688.0 126.0 3.5 6.1 Finance 12156.7 1345.5 680.7 106.6 9.4 39.2 HiTech 3982.6 4196.0 3946.8 313.9 64.3 13.5 Finance 8760.7 886.4 1006.9 90.0 7.5 28.5 Manufacturing 2362.2 3153.3 1080.0 137.0 25.2 8.4 Transportation 2499.9 3419.0 992.6 47.2 25.3 8.8 Energy 1430.4 1610.0 664.3 77.7 3.5 5.4 Energy 13666.5 15465.4 2736.7 411.4 26.6 43.9 Manufacturing 4069.3 4174.7 2907.6 289.2 38.2 13.7 Energy 2924.7 711.9 1067.8 146.7 3.4 10.1 Transportation 1262.1 1716.0 364.3 71.2 14.5 4.9 Medical 684.4 672.9 287.4 61.8 6.0 3.1 Energy 3069.3 1719.0 1439.0 196.4 4.9 10.6 Medical 246.5 318.8 924.1 43.8 3.1 1.7 Finance 11562.2 1128.5 580.4 64.2 6.7 37.3 Finance 9316.0 1059.4 816.5 95.9 8.0 30.2 Retail 1094.3 3848.0 563.3 29.4 44.7 4.4 Retail 1102.1 4878.3 932.4 65.2 47.3 4.4 HiTech 466.4 675.8 845.7 64.5 5.2 2.4 Manufacturing 10839.4 5468.7 1895.4 232.8 47.8 35.0 Manufacturing 733.5 2135.3 96.6 10.9 2.7 3.2 Manufacturing 10354.2 14477.4 5607.2 321.9 188.5 33.5 Energy 1902.1 2697.9 329.3 34.2 2.2 6.9 Other 2245.2 2132.2 2230.4 198.9 8.0 8.0 Transportation 949.4 1248.3 298.9 35.4 10.4 3.9 Retail 2834.4 2884.6 458.2 41.2 49.8 9.8 Retail 2621.1 6173.8 1992.7 183.7 115.1 9.2 ;
For each company in your sample, the variables are defined as follows:
Type identifies the type of market for the company.
Asset contains the company’s assets, in millions of dollars.
Sale contains sales, in millions of dollars.
Value contains the market value of the company, in millions of dollars.
Profit contains the profit, in millions of dollars.
Employee contains the number of employees, in thousands.
Weight contains the sampling weight.
The following SAS statements use PROC SURVEYMEANS to perform the domain analysis, estimating means, and other statistics for the overall population and also for the subpopulations (or domain) defined by market type. The DOMAIN statement specifies Type as the domain variable:
title 'Top Companies Profile Study'; proc surveymeans data=Company total=800 mean sum; var Asset Sale Value Profit Employee; weight Weight; domain Type; run;
Output 88.2.1 shows that there are 66 observations in the sample. The sum of the sampling weights equals 799.8, which is close to the total number of companies in the study population.
| Top Companies Profile Study |
| Data Summary | |
|---|---|
| Number of Observations | 66 |
| Sum of Weights | 799.8 |
| Statistics | ||||
|---|---|---|---|---|
| Variable | Mean | Std Error of Mean | Sum | Std Dev |
| Asset | 6523.488510 | 720.557075 | 5217486 | 1073829 |
| Sale | 4215.995799 | 839.132506 | 3371953 | 847885 |
| Value | 2145.935121 | 342.531720 | 1716319 | 359609 |
| Profit | 188.788210 | 25.057876 | 150993 | 30144 |
| Employee | 36.874869 | 7.787857 | 29493 | 7148.003298 |
The "Statistics" table in Output 88.2.1 displays the estimates of the mean and total for all analysis variables for the entire set of 800 companies, while Output 88.2.2 shows the mean and total estimates for each company type.
| Domain Analysis: Type | |||||
|---|---|---|---|---|---|
| Type | Variable | Mean | Std Error of Mean | Sum | Std Dev |
| Energy | Asset | 7868.302932 | 1941.699163 | 1449341 | 785962 |
| Sale | 5419.679099 | 2416.214417 | 998305 | 673373 | |
| Value | 2249.297177 | 520.295162 | 414321 | 213580 | |
| Profit | 289.564658 | 52.512141 | 53338 | 25927 | |
| Employee | 14.151194 | 3.974697 | 2606.650000 | 1481.777769 | |
| Finance | Asset | 7890.190264 | 1057.185336 | 1855773 | 704506 |
| Sale | 829.210502 | 115.762531 | 195030 | 74436 | |
| Value | 565.068197 | 76.964547 | 132904 | 48156 | |
| Profit | 63.716837 | 10.099341 | 14986 | 5801.108513 | |
| Employee | 5.806293 | 0.811555 | 1365.640000 | 519.658410 | |
| HiTech | Asset | 5031.959781 | 732.436967 | 321542 | 183302 |
| Sale | 5464.292019 | 731.296997 | 349168 | 196013 | |
| Value | 6707.828482 | 1194.160584 | 428630 | 249154 | |
| Profit | 346.407042 | 42.299004 | 22135 | 12223 | |
| Employee | 70.766980 | 8.683595 | 4522.010000 | 2524.778281 | |
| Manufacturing | Asset | 7403.004250 | 1454.921083 | 888361 | 492577 |
| Sale | 7207.638833 | 2112.444703 | 864917 | 501679 | |
| Value | 2986.442750 | 799.121544 | 358373 | 196979 | |
| Profit | 211.933583 | 39.993255 | 25432 | 13322 | |
| Employee | 83.314333 | 31.089019 | 9997.720000 | 6294.309490 | |
| Medical | Asset | 5046.570609 | 1218.444638 | 140799 | 131942 |
| Sale | 3313.219713 | 758.216303 | 92439 | 85655 | |
| Value | 2561.614695 | 530.802245 | 71469 | 64663 | |
| Profit | 218.682796 | 44.051447 | 6101.250000 | 5509.560969 | |
| Employee | 46.518996 | 11.135955 | 1297.880000 | 1213.651734 | |
| Other | Asset | 1850.250000 | 338.128984 | 58838 | 31375 |
| Sale | 1620.784906 | 168.686773 | 51541 | 24593 | |
| Value | 1432.820755 | 297.869828 | 45564 | 24204 | |
| Profit | 115.089937 | 27.970560 | 3659.860000 | 2018.201371 | |
| Employee | 14.306604 | 2.313733 | 454.950000 | 216.327710 | |
| Retail | Asset | 2939.845750 | 393.692369 | 235188 | 94605 |
| Sale | 7395.453500 | 1746.187580 | 591636 | 263263 | |
| Value | 2103.863125 | 529.756409 | 168309 | 78304 | |
| Profit | 157.171875 | 31.734253 | 12574 | 5478.281027 | |
| Employee | 93.624000 | 15.726743 | 7489.920000 | 3093.832061 | |
| Transportation | Asset | 4712.047359 | 888.954411 | 267644 | 163516 |
| Sale | 4030.233275 | 1015.555708 | 228917 | 142669 | |
| Value | 1703.330282 | 313.841326 | 96749 | 58947 | |
| Profit | 224.762324 | 56.168925 | 12767 | 8287.585418 | |
| Employee | 30.946303 | 6.786270 | 1757.750000 | 1066.586615 | |