Help the Stat Consulting Group by
giving a gift
Loading
|
|
|
||||
|
Help the Stat Consulting Group by
giving a gift
| |||||
|
Loading
|
|||||
The examples below use Stata 8. If you are using Stata version 9, please see this page.This example is taken from Levy and Lemeshow's Sampling of Populations.
page 53 simple random sampling
use http://www.ats.ucla.edu/stat/books/sop/momsag.dta, clear
svyset [pweight=weight1], fpc(birth)
svymean momsag
Survey mean estimation
pweight: weight1 Number of obs = 25
Strata: <one> Number of strata = 1
PSU: <observations> Number of PSUs = 25
FPC: birth Population size = 773
------------------------------------------------------------------------------
Mean | Estimate Std. Err. [95% Conf. Interval] Deff
---------+--------------------------------------------------------------------
momsag | .92 .0544746 .8075699 1.03243 1
------------------------------------------------------------------------------
Finite population correction (FPC) assumes simple random sampling without
replacement of PSUs within each stratum with no subsampling within PSUs.
Weights must represent population totals for deff to be correct when
using an FPC. Note: deft is invariant to the scale of weights.
svytotal momsag Survey total estimation pweight: weight1 Number of obs = 25 Strata: <one> Number of strata = 1 PSU: <observations> Number of PSUs = 25 FPC: birth Population size = 773 ------------------------------------------------------------------------------ Total | Estimate Std. Err. [95% Conf. Interval] Deff ---------+-------------------------------------------------------------------- momsag | 711.16 42.10889 624.2515 798.0685 1 ------------------------------------------------------------------------------ Finite population correction (FPC) assumes simple random sampling without replacement of PSUs within each stratum with no subsampling within PSUs. Weights must represent population totals for deff to be correct when using an FPC. Note: deft is invariant to the scale of weights.
This example is taken from Lehtonen and Pahkinen's Practical Methods for Design and Analysis of Complex Surveys.
page 29 Table 2.4 Estimates from a simple random sample drawn without replacement (n = 8); the Province'91 population.
input id cluster ue91 lab91 1 1 4123 33786 2 4 760 5919 3 5 721 4930 4 15 142 675 5 18 187 1448 6 26 331 2543 7 30 127 1084 8 31 219 1330 end gen fpc = 32 gen wt = 4 gen strata = 1 svyset [pweight=wt], psu(cluster) svytotal ue91 svyratio ue91 lab91
Survey total estimation
pweight: wt Number of obs = 8
Strata: <one> Number of strata = 1
PSU: cluster Number of PSUs = 8
Population size = 32
------------------------------------------------------------------------------
Total | Estimate Std. Err. [95% Conf. Interval] Deff
---------+--------------------------------------------------------------------
ue91 | 26440 15337.03 -9826.316 62706.32 1
------------------------------------------------------------------------------
Survey ratio estimation
pweight: wt Number of obs = 8
Strata: <one> Number of strata = 1
PSU: cluster Number of PSUs = 8
Population size = 32
------------------------------------------------------------------------------
Ratio | Estimate Std. Err. [95% Conf. Interval] Deff
------------------+-----------------------------------------------------------
ue91/lab91 | .1278159 .0047196 .1166559 .1389759 1
------------------------------------------------------------------------------
UCLA Researchers are invited to our Statistical Consulting Services
We recommend others to our list of Other Resources for Statistical Computing Help
These pages are Copyrighted (c) by UCLA Academic Technology Services