This example is taken from Levy and Lemeshow’s Sampling of Populations.
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 | ------------------------------------------------------------------------------------
This example is taken from Lehtonen and Pahkinen’s Practical Methods for Design and Analysis of Complex Surveys.
page 74 Table 3.3 Estimates from an optimally allocated stratified simple random sample (n = 8); the Province’91 population. NOTE: In this data set, the fpc changes with the strata. This is different from all of the previous examples.
data page74; input id str clu wt ue91 lab91 fpc; datalines; 1 1 1 1.75 4123 33786 7 2 1 2 1.75 666 6016 7 3 1 4 1.75 760 5919 7 4 1 6 1.75 457 3022 7 5 2 21 6.25 61 573 25 6 2 25 6.25 262 1737 25 7 2 26 6.25 331 2543 25 8 2 27 6.25 98 545 25 ; run; proc descript data = page74 filetype = sas design = wor deft4 totals; weight wt; nest str; var ue91; totcnt fpc; run;
Number of observations read : 8 Weighted count : 32 Denominator degrees of freedom : 6 Variance Estimation Method: Taylor Series (WOR) by: Variable, One. ----------------------------------------------------- | | | | Variable | | One | | | 1 | ----------------------------------------------------- | | | | | UE91 | Sample Size | 8 | | | Weighted Size | 32.00 | | | Total | 15210.50 | | | SE Total | 4279.45 | | | Mean | 475.33 | | | SE Mean | 133.73 | | | DEFF Mean #4 | 0.15 | | | DEFF Total #4 | 0.15 | -----------------------------------------------------
proc ratio data = page74 filetype = sas design = strwor; weight wt; nest str; totcnt fpc; numer ue91; denom lab91; run;
Number of observations read : 8 Weighted count : 32 Denominator degrees of freedom : 6 Variance Estimation Method: Taylor Series (STRWOR) by: Variable, One. --------------------------------------------------- | | | | Variable | | One | | | 1 | --------------------------------------------------- | | | | | UE91/LAB91 | Sample Size | 8 | | | Weighted Size | 32.00 | | | Weighted X-Sum | 119037.75 | | | Weighted Y-Sum | 15210.50 | | | Ratio Est. | 0.13 | | | SE Ratio | 0.00 | ---------------------------------------------------
proc descript data = page74 filetype = sas design = strwor; weight wt; nest str; var ue91; totcnt fpc; percentile / median; run;
Cannot extrapolate to compute confidence limit for 50.00th percentile. Generating a missing value. Number of observations read : 8 Weighted count : 32 Denominator degrees of freedom : 6 Variance Estimation Method: Taylor Series (WOR) by: Variable, One, Percentiles. for: Variable = UE91. ----------------------------------------------------------------------------------- One Sample Weighted Lower 95% Upper 95% Percentiles Size Size Quantile Limit Limit ----------------------------------------------------------------------------------- 1 50.00 8 32.00 189.84 . 300.36 ----------------------------------------------------------------------------------- --------------------------------- One SE Percentiles Quantile --------------------------------- 1 50.00 . ---------------------------------