Chapter 3: Simple random sampling
page 53 simple random sampling
This example uses the momsag data set.
The _one_ on the nest statement tells SUDAAN that the entire sample is "at the same level" – in other words, the entire sample is in the same stratum. _one_ is a SUDAAN keyword and not a variable in the data set. You can use the samcnt statement to check to see if SUDAAN calculates the same number of observations as you think is in the data set (see page 105 in the SUDAAN manual). The totcnt statement computes the fpc (i.e., finite population correction), which is why it is the same variable used as the fpc in Stata.
proc descript data = momsag filetype = sas design = wor total ; weight weight1; nest _one_; totcnt birth; var momsag; run; Number of observations read : 25 Weighted count : 773 Denominator degrees of freedom : 24 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ----------------------------------------------------- | | | | Variable | | One | | | 1 | ----------------------------------------------------- | | | | | MOMSAG | Sample Size | 25 | | | Weighted Size | 773.00 | | | Total | 711.16 | | | SE Total | 42.11 | | | Mean | 0.92 | | | SE Mean | 0.05 | -----------------------------------------------------
Chapter 4: Systematic sampling
page 109 repeated systematic sampling
This example uses the wloss2 data set.
proc descript data = wloss2 filetype=sas design = wor means totals; nest _one_ cluster; weight wt1; totcnt m _zero_; var xi; setenv colwidth = 15; setenv decwidth = 3; run; Number of observations read : 18 Weighted count : 162 Denominator degrees of freedom : 5 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. -------------------------------------------------------- | | | | Variable | | One | | | 1 | -------------------------------------------------------- | | | | | XI | Sample Size | 18.000 | | | Weighted Size | 162.000 | | | Total | 729.000 | | | SE Total | 85.949 | | | Mean | 4.500 | | | SE Mean | 0.531 | --------------------------------------------------------
Chapter 5: Stratification and stratified random sampling
page 138 stratification and stratified random sampling
This example uses the hospsamp data set.
proc descript data = hospsamp filetype = sas design = wor totals; nest oblevel; weight weighta; totcnt tothosp; var births; subgroup oblevel; levels 3; setenv colwidth = 20; setenv decwidth = 3; run;
Number of observations read : 15 Weighted count : 158 Denominator degrees of freedom : 12 Variance Estimation Method: Taylor Series (WOR) by: Variable, OBLEVEL. ------------------------------------------------------------------------------------ | | | | Variable | | OBLEVEL | | | Total | 1 | ------------------------------------------------------------------------------------ | | | | | | BIRTHS | Sample Size | 15.000 | 4.000 | | | Weighted Size | 158.000 | 42.000 | | | Total | 183982.904 | 14931.000 | | | SE Total | 34014.329 | 2669.857 | | | Mean | 1164.449 | 355.500 | | | SE Mean | 215.281 | 63.568 | ------------------------------------------------------------------------------------ Variance Estimation Method: Taylor Series (WOR) by: Variable, OBLEVEL. ------------------------------------------------------------------------------------ | | | | Variable | | OBLEVEL | | | 2 | 3 | ------------------------------------------------------------------------------------ | | | | | | BIRTHS | Sample Size | 5.000 | 6.000 | | | Weighted Size | 99.000 | 17.000 | | | Total | 117116.928 | 51934.977 | | | SE Total | 33067.664 | 7508.399 | | | Mean | 1183.000 | 3055.000 | | | SE Mean | 334.017 | 441.671 | ------------------------------------------------------------------------------------
Chapter 6: Stratified random sampling: Further issues
page 167 stratified random sampling: allocation of sample to strata
This example uses the jacktwn data set.
proc descript data = jacktwn filetype = sas means totals design = strwor; nest stratum; weight sampwt; totcnt npop; setenv decwidth = 3; subgroup quart1; levels 3; tables quart1; var twin; run;
Number of observations read : 831 Weighted count : 256998 Denominator degrees of freedom : 813 Variance Estimation Method: Taylor Series (STRWOR) by: Variable, QUART1. ----------------------------------------------------------------------------------- | | | | Variable | | QUART1 | | | Total | 1 | 2 | ----------------------------------------------------------------------------------- | | | | | | | TWIN | Sample Size | 831.000 | 329.000 | 369.000 | | | Weighted Size | 256998.000 | 63937.000 | 127874.000 | | | Total | 26055.397 | 19183.803 | 6737.907 | | | SE Total | 3791.044 | 2661.629 | 2696.605 | | | Mean | 0.101 | 0.300 | 0.053 | | | SE Mean | 0.015 | 0.042 | 0.021 | ----------------------------------------------------------------------------------- Variance Estimation Method: Taylor Series (STRWOR) by: Variable, QUART1. ----------------------------------------------------- | | | | Variable | | QUART1 | | | 3 | ----------------------------------------------------- | | | | | TWIN | Sample Size | 133.000 | | | Weighted Size | 65187.000 | | | Total | 133.687 | | | SE Total | 126.744 | | | Mean | 0.002 | | | SE Mean | 0.002 | -----------------------------------------------------
page 173 stratified random sampling: Stratification after sampling
This example uses the dogcats data set.
proc descript data = dogscats filetype=sas design=wor; nest _one_; totcnt n; weight weight; subgroup type; levels 2; var totexp; postvar type; postwgt 850 450; run;
Number of observations read : 50 Weighted count : 1300 Denominator degrees of freedom : 49 Variance Estimation Method: Taylor Series (WOR) Post-stratified estimates by: Variable, TYPE. ----------------------------------------------------------------------------------- | | | | Variable | | TYPE | | | Total | 1 | 2 | ----------------------------------------------------------------------------------- | | | | | | | TOTEXP | Sample Size | 50 | 32 | 18 | | | Weighted Size | 1300.00 | 850.00 | 450.00 | | | Total | 52149.67 | 42379.67 | 9770.00 | | | Mean | 40.12 | 49.86 | 21.71 | | | SE Mean | 1.16 | 1.44 | 1.97 | -----------------------------------------------------------------------------------
Chapter 7: Ratio estimation
page 198 ratio estimation
This example uses the tab7pt1 data set. Note that there may be a typo in the text for the weighted X-sum and the weighted Y-sum.
proc ratio data = tab7pt1 filetype = sas design=strwor; totcnt totcnt; weight wt1; nest _one_; numer pharmexp; denom totmedex; setenv colwidth = 1; setenv decwidth = 4; run;
Number of observations read : 7 Weighted count : 8 Denominator degrees of freedom : 6 Variance Estimation Method: Taylor Series (STRWOR) by: Variable, One. --------------------------------------------------- | | | | Variable | | One | | | 1 | --------------------------------------------------- | | | | | PHARMEXP/TOTME- | Sample Size | 7 | | DEX | Weighted Size | 8.00 | | | Weighted X-Sum | 3222857.14 | | | Weighted Y-Sum | 1028571.43 | | | Ratio Est. | 0.32 | | | SE Ratio | 0.00 | ---------------------------------------------------
Chapter 9: Simple one-stage cluster sampling
page 250 simple one-stage cluster sampling
This example uses the tab9_1c data set.
proc descript data = tab9_1c filetype =sas design = wor means totals; nest _one_ devlpmnt; totcnt m _zero_; weight wt1; var nge65 nvstnrs hhneedvn; setenv colwidth = 13 decwidth = 5; run;
Number of observations read : 40 Weighted count : 100 Denominator degrees of freedom : 1 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | NGE65 | Sample Size | 40.00000 | | | Weighted Size | 100.00000 | | | Total | 167.50000 | | | SE Total | 1.93649 | | | Mean | 1.67500 | | | SE Mean | 0.01936 | ------------------------------------------------------ | | | | | NVSTNRS | Sample Size | 40.00000 | | | Weighted Size | 100.00000 | | | Total | 57.50000 | | | SE Total | 1.93649 | | | Mean | 0.57500 | | | SE Mean | 0.01936 | ------------------------------------------------------ | | | | | HHNEEDVN | Sample Size | 40.00000 | | | Weighted Size | 100.00000 | | | Total | 52.50000 | | | SE Total | 1.93649 | | | Mean | 0.52500 | | | SE Mean | 0.01936 | ------------------------------------------------------ proc ratio data = tab9_1c filetype = sas design = wor; nest _one_ devlpmnt; totcnt M _zero_; weight wt1; numer nvstnrs; denom nge65; setenv colwidth = 13 decwidth = 5; run;
Number of observations read : 40 Weighted count : 100 Denominator degrees of freedom : 1 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | NVSTNRS/NGE65 | Sample Size | 40.00000 | | | Weighted Size | 100.00000 | | | Weighted X-Sum | 167.50000 | | | Weighted Y-Sum | 57.50000 | | | Ratio Est. | 0.34328 | | | SE Ratio | 0.00759 | ------------------------------------------------------
page 253 simple one-stage cluster sampling
data probbksm; input record district eligible treated w n; cards; 1 6 486 79 2.6 26 2 10 240 94 2.6 26 3 14 428 17 2.6 26 4 15 343 57 2.6 26 5 17 1130 63 2.6 26 6 19 983 10 2.6 26 7 20 333 58 2.6 26 8 21 13 0 2.6 26 9 22 1506 101 2.6 26 10 25 1755 411 2.6 26 ; run; proc ratio data = probbksm filetype = sas design=strwor; nest _one_; totcnt n; weight w; numer treated; denom eligible; setenv colwidth = 13; setenv decwidth = 3; run;
Number of observations read : 10 Weighted count : 26 Denominator degrees of freedom : 9 Variance Estimation Method: Taylor Series (STRWOR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | TREATED/ELIGIB- | Sample Size | 10.000 | | LE | Weighted Size | 26.000 | | | Weighted X-Sum | 18764.200 | | | Weighted Y-Sum | 2314.000 | | | Ratio Est. | 0.123 | | | SE Ratio | 0.030 | ------------------------------------------------------
Chapter 10: Two-stage cluster sampling: Clusters sampled with equal probability
page 285 two-stage cluster sampling: clusters sample with equal probability and all of the clusters have the same n and without replacement
data pt1; input center nurse m nbar w npatnts nrefrred; cards; 1 2 5 3 2.5 44 6 1 3 5 3 2.5 18 6 2 1 5 3 2.5 42 3 2 3 5 3 2.5 10 2 4 1 5 3 2.5 16 5 4 2 5 3 2.5 32 14 ; run;
The proc descript and the proc ratio below give the second to last column of the table on page 287.
proc descript data = pt1 filetype = sas design = wor means totals; nest _one_ center; weight w; totcnt m nbar; var npatnts nrefrred; setenv colwidth = 13; setenv decwidth = 3; run;
Number of observations read : 6 Weighted count : 15 Denominator degrees of freedom : 2 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | NPATNTS | Sample Size | 6.000 | | | Weighted Size | 15.000 | | | Total | 405.000 | | | SE Total | 53.245 | | | Mean | 27.000 | | | SE Mean | 3.550 | ------------------------------------------------------ | | | | | NREFRRED | Sample Size | 6.000 | | | Weighted Size | 15.000 | | | Total | 90.000 | | | SE Total | 21.679 | | | Mean | 6.000 | | | SE Mean | 1.445 | ------------------------------------------------------ proc ratio data = pt1 filetype = sas design =wor; nest _one_ center; weight w; totcnt m nbar; numer nrefrred; denom npatnts; setevn colwidth = 13; setenv decwidth = 3; run;
Number of observations read : 6 Weighted count : 15 Denominator degrees of freedom : 2 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | NREFRRED/NPATN- | Sample Size | 6.000 | | TS | Weighted Size | 15.000 | | | Weighted X-Sum | 405.000 | | | Weighted Y-Sum | 90.000 | | | Ratio Est. | 0.222 | | | SE Ratio | 0.058 | ------------------------------------------------------
The proc descript and the proc ratio below gives the values in the last column of the table on page 287.
page 286 two-stage cluster sampling: clusters sampled with equal probability, all clusters have the same n and sampling is with replacement (or the sampling fractions are small at each stage)
proc descript data = pt1 filetype = sas design = wr means totals; nest _one_ center; weight w; var npatnts nrefrred; setenv colwidth = 13; setenv decwidth = 3; run;
Number of observations read : 6 Weighted count : 15 Denominator degrees of freedom : 2 Variance Estimation Method: Taylor Series (WR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | NPATNTS | Sample Size | 6.000 | | | Weighted Size | 15.000 | | | Total | 405.000 | | | SE Total | 31.225 | | | Mean | 27.000 | | | SE Mean | 2.082 | ------------------------------------------------------ | | | | | NREFRRED | Sample Size | 6.000 | | | Weighted Size | 15.000 | | | Total | 90.000 | | | SE Total | 30.311 | | | Mean | 6.000 | | | SE Mean | 2.021 | ------------------------------------------------------
proc ratio data = pt1 filetype = sas design = wr; nest _one_ center; weight w; numer nrefrred; denom npatnts; setenv colwidth = 13; setevn decwidth = 3; run;
Number of observations read : 6 Weighted count : 15 Denominator degrees of freedom : 2 Variance Estimation Method: Taylor Series (WR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | NREFRRED/NPATN- | Sample Size | 6.000 | | TS | Weighted Size | 15.000 | | | Weighted X-Sum | 405.000 | | | Weighted Y-Sum | 90.000 | | | Ratio Est. | 0.222 | | | SE Ratio | 0.081 | ------------------------------------------------------
page 310 two-stage cluster sampling: clusters sampled with equal probability in which not all clusters have the same
This example uses the pt210 data set.
proc descript data = pt210 filetype = sas design = wor means totals; nest _one_ hospno; weight w; totcnt m ni; var dxdead liefthrt; setenv colwidth = 13; setenv decwidth = 3; run;
Number of observations read : 708 Weighted count : 23600 Denominator degrees of freedom : 2 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | DXDEAD | Sample Size | 708.000 | | | Weighted Size | 23599.988 | | | Total | 499.379 | | | SE Total | 116.072 | | | Mean | 0.021 | | | SE Mean | 0.011 | ------------------------------------------------------ | | | | | LIFETHRT | Sample Size | 708.000 | | | Weighted Size | 23599.988 | | | Total | 2932.319 | | | SE Total | 773.082 | | | Mean | 0.124 | | | SE Mean | 0.018 | ------------------------------------------------------
proc ratio data = pt210 filetype = sas design = wor; nest _one_ hospno; weight w; totcnt m ni; numer dxdead; denom lifethrt; setenv colwidth = 13; setenv decwidth = 3; run;
Number of observations read : 708 Weighted count : 23600 Denominator degrees of freedom : 2 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ------------------------------------------------------ | | | | Variable | | One | | | 1 | ------------------------------------------------------ | | | | | DXDEAD/LIFETHRT | Sample Size | 708.000 | | | Weighted Size | 23599.988 | | | Weighted X-Sum | 2932.319 | | | Weighted Y-Sum | 499.379 | | | Ratio Est. | 0.170 | | | SE Ratio | 0.064 | ------------------------------------------------------
Chapter 11: Cluster sampling in which clusters are sampled with unequal probability: Probability proportional to size sampling
page 350 cluster sampling with unequal probabilities: probability proportional to size sampling
This example uses the hospslct data set.
proc descript data = hospslct filetype=sas design = wr means totals; nest drawing/psulev = 1; weight wstar; var lifethrt dxdead; run;
Number of observations read : 50 Weighted count : 50056 Denominator degrees of freedom : 4 Variance Estimation Method: Taylor Series (WR) by: Variable, One. ----------------------------------------------------- | | | | Variable | | One | | | 1 | ----------------------------------------------------- | | | | | LIFETHRT | Sample Size | 50 | | | Weighted Size | 50056.00 | | | Total | 6006.72 | | | SE Total | 1001.12 | | | Mean | 0.12 | | | SE Mean | 0.02 | ----------------------------------------------------- | | | | | DXDEAD | Sample Size | 50 | | | Weighted Size | 50056.00 | | | Total | 2002.24 | | | SE Total | 1226.12 | | | Mean | 0.04 | | | SE Mean | 0.02 | -----------------------------------------------------
proc ratio data = hospslct filetype = sas design = wr; nest drawing / psulev =1; weight wstar; numer dxdead; denom lifethrt; run;
Number of observations read : 50 Weighted count : 50056 Denominator degrees of freedom : 4 Variance Estimation Method: Taylor Series (WR) by: Variable, One. --------------------------------------------------- | | | | Variable | | One | | | 1 | --------------------------------------------------- | | | | | DXDEAD/LIFETHRT | Sample Size | 50 | | | Weighted Size | 50056.00 | | | Weighted X-Sum | 6006.72 | | | Weighted Y-Sum | 2002.24 | | | Ratio Est. | 0.33 | | | SE Ratio | 0.23 | ---------------------------------------------------
Page 353 cluster sampling with unequal probabilities: probability proportional to size sampling
data hspslct2; set hospslct; /*n is 50*/ /*N_i is admiss*/ /* X is 7087, the total number of life-threating conditions across all the hospitals*/ /*X_i is tl, the total number of life-threating conditions for each hospital*/ if hospno = 2 then tl = 785; if hospno = 5 then tl = 3404; if hospno = 9 then tl = 778; w2star = (admiss/50)*(7087/tl); run; proc descript data = hspslct2 filetype = sas means totals; nest drawing/psulev=1; weight w2star; var lifethrt dxdead; run;
Number of observations read : 50 Weighted count : 51345 Denominator degrees of freedom : 4
Variance Estimation Method: Taylor Series (WR) by: Variable, One. ----------------------------------------------------- | | | | Variable | | One | | | 1 | ----------------------------------------------------- | | | | | LIFETHRT | Sample Size | 50 | | | Weighted Size | 51345.00 | | | Total | 6259.18 | | | SE Total | 1277.32 | | | Mean | 0.12 | | | SE Mean | 0.02 | ----------------------------------------------------- | | | | | DXDEAD | Sample Size | 50 | | | Weighted Size | 51345.00 | | | Total | 1760.47 | | | SE Total | 1079.04 | | | Mean | 0.03 | | | SE Mean | 0.02 | -----------------------------------------------------
proc ratio data = hspslct2 filetype = sas; nest drawing/psulev=1; weight w2star; numer dxdead; denom lifethrt; run;
Number of observations read : 50 Weighted count : 51345 Denominator degrees of freedom : 4 Variance Estimation Method: Taylor Series (WR) by: Variable, One. --------------------------------------------------- | | | | Variable | | One | | | 1 | --------------------------------------------------- | | | | | DXDEAD/LIFETHRT | Sample Size | 50 | | | Weighted Size | 51345.00 | | | Weighted X-Sum | 6259.18 | | | Weighted Y-Sum | 1760.47 | | | Ratio Est. | 0.28 | | | SE Ratio | 0.21 | ---------------------------------------------------
Chapter 12: Variance estimation in complex sample surveys
page 370 variance estimation in complex sample surveys: linearization
This example uses the exmp12_2 data set.
proc ratio data = exmp12_2 filetype = sas design = wor; nest _one_; weight w; totcnt n; numer ovpaymnt; denom payment; setenv colwidth = 15; setenv decwidth = 3; run;
Number of observations read : 10 Weighted count : 65 Denominator degrees of freedom : 9 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. -------------------------------------------------------- | | | | Variable | | One | | | 1 | -------------------------------------------------------- | | | | | OVPAYMNT/PAYME- | Sample Size | 10.000 | | NT | Weighted Size | 65.000 | | | Weighted X-Sum | 17914.000 | | | Weighted Y-Sum | 6922.500 | | | Ratio Est. | 0.386 | | | SE Ratio | 0.116 | --------------------------------------------------------
NOTE: The problem with the amblnce2 data file on the Wiley website is that the first variable does not have a name. To open the file, you need to use SAS 6.12 and use the viewer (which is not available in SAS 8.x). Add the name to the first variable and save the file. Use StatTransfer to make the file SAS 8.x format. Note that the data set is printed on page 377, except for the replicate weight variables.
page 376 variance estimation in complex sample surveys: replication methods
This example uses the am (amblnce2) data set.
proc ratio data = am filetype = sas design = brr; weight wt; repwgt repwt1 repwt4 repwt6 repwt7; numer alive; denom cardarrs; setenv colwidth = 14; setenv decwidth = 5; run;
Number of observations read : 6 Weighted count : 15 Denominator degrees of freedom : 4 Variance Estimation Method: BRR by: Variable, One. ------------------------------------------------------- | | | | Variable | | One | | | 1 | ------------------------------------------------------- | | | | | ALIVE/CARDARRS | Sample Size | 6.00000 | | | Weighted Size | 15.00000 | | | Weighted X-Sum | 4527.50000 | | | Weighted Y-Sum | 695.00000 | | | Ratio Est. | 0.15351 | | | SE Ratio | 0.00943 | -------------------------------------------------------
page 377 variance estimation in complex sample surveys: replication methods
proc ratio data = am filetype = sas design = strwor; nest esa; totcnt nambstat; weight wt; numer alive; denom cardarrs; setenv colwidth = 14; setenv decwidth = 5; run;
Number of observations read : 6 Weighted count : 15 Denominator degrees of freedom : 3 Variance Estimation Method: Taylor Series (STRWOR) by: Variable, One. ------------------------------------------------------- | | | | Variable | | One | | | 1 | ------------------------------------------------------- | | | | | ALIVE/CARDARRS | Sample Size | 6.00000 | | | Weighted Size | 15.00000 | | | Weighted X-Sum | 4527.50000 | | | Weighted Y-Sum | 695.00000 | | | Ratio Est. | 0.15351 | | | SE Ratio | 0.00760 | -------------------------------------------------------
page 379 variance estimation in complex sample surveys: replication methods
proc ratio data=am filetype = sas design =jackknife; nest esa; weight wt; numer alive; denom cardarrs; setenv colwidth = 14; setenv decwidth = 7; run;
Number of observations read : 6 Weighted count : 15 Denominator degrees of freedom : 3 Variance Estimation Method: Delete-1 Jackknife by: Variable, One. ------------------------------------------------------- | | | | Variable | | One | | | 1 | ------------------------------------------------------- | | | | | ALIVE/CARDARRS | Sample Size | 6.0000000 | | | Weighted Size | 15.0000000 | | | Weighted X-Sum | 4527.5000000 | | | Weighted Y-Sum | 695.0000000 | | | Ratio Est. | 0.1535064 | | | SE Ratio | 0.0098492 | -------------------------------------------------------
page 485 strategies for design-based analysis of sample survey data
data ch16; input id region nurshome patient medicaid rgnhomes nhadmiss ; weight = (rgnhomes*nhadmiss)/10; cards; 1 1 1 1 1 12 123 2 1 1 2 1 12 123 3 1 1 3 1 12 123 4 1 1 4 0 12 123 5 1 1 5 1 12 123 6 1 2 1 0 12 89 7 1 2 2 0 12 89 8 1 2 3 1 12 89 9 1 2 4 0 12 89 10 1 2 5 0 12 89 11 2 1 1 1 20 231 12 2 1 2 0 20 231 13 2 1 3 1 20 231 14 2 1 4 0 20 231 15 2 1 5 1 20 231 16 2 2 1 0 20 187 17 2 2 2 0 20 187 18 2 2 3 0 20 187 19 2 2 4 1 20 187 20 2 2 5 0 20 187 21 3 1 1 1 11 43 22 3 1 2 1 11 43 23 3 1 3 1 11 43 24 3 1 4 0 11 43 25 3 1 5 1 11 43 26 3 2 1 1 11 49 27 3 2 2 1 11 49 28 3 2 3 1 11 49 29 3 2 4 1 11 49 30 3 2 5 0 11 49 31 4 1 1 0 8 56 32 4 1 2 1 8 56 33 4 1 3 1 8 56 34 4 1 4 0 8 56 35 4 1 5 0 8 56 36 4 2 1 0 8 38 37 4 2 2 0 8 38 38 4 2 3 0 8 38 39 4 2 4 0 8 38 40 4 2 5 1 8 38 41 5 1 1 1 6 359 42 5 1 2 0 6 359 43 5 1 3 1 6 359 44 5 1 4 1 6 359 45 5 1 5 0 6 359 46 5 2 1 0 6 460 47 5 2 2 1 6 460 48 5 2 3 0 6 460 49 5 2 4 1 6 460 50 5 2 5 0 6 460 ; run;
proc descript data = ch16 filetype = sas design = wor deft4 deff totals; nest region nurshome; totcnt rgnhomes nhadmiss; var medicaid; weight weight; setenv colwidth = 15; setenv decwidth = 4; run;
Number of observations read : 50 Weighted count : 8791 Denominator degrees of freedom : 5 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. -------------------------------------------------------- | | | | Variable | | One | | | 1 | -------------------------------------------------------- | | | | | MEDICAID | Sample Size | 50.0000 | | | Weighted Size | 8791.0000 | | | Total | 4180.2000 | | | SE Total | 1112.7529 | | | Mean | 0.4755 | | | SE Mean | 0.1052 | | | DEFF Mean #4 | 2.1748 | | | DEFF Total #4 | 3.1479 | --------------------------------------------------------