NOTE: If you want to see the design effect or the misspecification effect, use estat effects after the command.
This example is taken from Lehtonen and Pahkinen’s Practical Methods for Design and Analysis of Complex Surveys.
This example provides the numbers necessary to use the formula in the middle of page 106. The svyreg is run to get the coefficient of hou85 and the svytotal is run to get the estimated total of hou85. These numbers are used in the formula and the result (15312) is shown in the last line of Table 3.14 on page 107.
input id str clu wt ue91 hou85 gwt adjwt smplrat 1 1 1 4 4123 26881 .5562 2.2248 .25 2 1 4 4 760 4896 .5562 2.2248 .25 3 1 5 4 721 3730 .5562 2.2248 .25 4 1 15 4 142 556 .5562 2.2248 .25 5 1 18 4 187 1463 .5562 2.2248 .25 6 1 26 4 331 1946 .5562 2.2248 .25 7 1 30 4 127 834 .5562 2.2248 .25 8 1 31 4 219 932 .5562 2.2248 .25 end
gen fpc = 32
svy: reg ue91 hou85
(running regress on estimation sample)
Survey: Linear regression
Number of strata = 1 Number of obs = 8
Number of PSUs = 8 Population size = 32
Design df = 7
F( 1, 7) = 44949.18
Prob > F = 0.0000
R-squared = 0.9982
------------------------------------------------------------------------------
| Linearized
ue91 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
hou85 | .1520142 .000717 212.01 0.000 .1503188 .1537097
_cons | 42.65468 20.54033 2.08 0.076 -5.915492 91.22485
------------------------------------------------------------------------------
svy: total hou85
(running total on estimation sample)
Survey: Total estimation
Number of strata = 1 Number of obs = 8
Number of PSUs = 8 Population size = 32
Design df = 7
--------------------------------------------------------------
| Linearized
| Total Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
hou85 | 164952 87298.57 -41476.32 371380.3
--------------------------------------------------------------