NOTE: If you want to see the design effect or the misspecification effect, use estat effects after the command.
Page 96 at the bottom
use https://stats.idre.ucla.edu/stat/stata/examples/lohr/agstrat.dta, clear sort region by region: count --------------------------------------------------------------------------------------------------- -> region = NC 103 --------------------------------------------------------------------------------------------------- -> region = NE 21 --------------------------------------------------------------------------------------------------- -> region = S 135 --------------------------------------------------------------------------------------------------- -> region = W 41
Page 97, figure 4.1
graph box acres92, over(region) ylabel( , nogrid) ytitle(Millions of Acres)
Page 97 table at the bottom
NOTE: The format option is used here so that the numbers are not displayed in scientific notation.
tabstat acres92, s(n mean var) by(region) format(%14.0g)
Summary for variables: acres92
by categories of: region
region | N mean variance
-------------+------------------------------
NC | 103 300504.15534 29618183543.3
NE | 21 97629.8095238 7647472708.16
S | 135 211315.044444 53587487856.2
W | 41 662295.512195 396185950266
-------------+------------------------------
Total | 300 295612.67 112039472103
--------------------------------------------
Page 98
NOTE: We need to make a numeric version of region for use with the svy: total command. The numbers listed in the column labeled “Estimate” are the same as those in the text in the column labeled “Estimated Total of Farm Acres”. The second svytotal command is used to get the overall total.
svyset [pweight=weight]
gen regionnum = 1 replace regionnum = 2 if region == "NE" replace regionnum = 3 if region == "S" replace regionnum = 4 if region == "W"
svy: total acres92, over(regionnum)
(running total on estimation sample)
Survey: Total estimation
Number of strata = 1 Number of obs = 300
Number of PSUs = 300 Population size = 3078
Design df = 299
1: regionnum = 1
2: regionnum = 2
3: regionnum = 3
4: regionnum = 4
--------------------------------------------------------------
| Linearized
Over | Total Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
acres92 |
1 | 3.17e+08 3.10e+07 2.56e+08 3.78e+08
2 | 2.15e+07 6110730 9453072 3.35e+07
3 | 2.92e+08 3.32e+07 2.27e+08 3.57e+08
4 | 2.79e+08 5.77e+07 1.66e+08 3.93e+08
--------------------------------------------------------------
svy: total acres92
(running total on estimation sample)
Survey: Total estimation
Number of strata = 1 Number of obs = 300
Number of PSUs = 300 Population size = 3078
Design df = 299
--------------------------------------------------------------
| Linearized
| Total Std. Err. [95% Conf. Interval]
-------------+------------------------------------------------
acres92 | 9.10e+08 5.96e+07 7.92e+08 1.03e+09
--------------------------------------------------------------
Page 102 Table 4.2
clear
input str18 discipline membership num_mailed valid_ret pct_female
"Literature" 9100 915 636 38
"Classics" 1950 633 451 27
"Philosophy" 5500 658 481 18
"History" 10850 855 611 19
"Linguistics" 2100 667 493 36
"Political Science" 5500 833 575 13
"Sociology" 9000 824 588 26
end
list
+---------------------------------------------------------------+
| discipline member~p num_ma~d valid_~t pct_fe~e |
|---------------------------------------------------------------|
1. | Literature 9100 915 636 38 |
2. | Classics 1950 633 451 27 |
3. | Philosophy 5500 658 481 18 |
4. | History 10850 855 611 19 |
5. | Linguistics 2100 667 493 36 |
|---------------------------------------------------------------|
6. | Political Science 5500 833 575 13 |
7. | Sociology 9000 824 588 26 |
+---------------------------------------------------------------+
tabstat membership num_mailed valid_ret, s(sum)
stats | member~p num_ma~d valid_~t
---------+------------------------------
sum | 44000 5385 3835
----------------------------------------
Page 104 in the middle
NOTE: The slight difference between this result and that shown in the text is probably due to rounding error.
use https://stats.idre.ucla.edu/stat/stata/examples/lohr/agstrat.dta, clear
gen newwt = 220/21 if region == "NE"
replace newwt = 1054/103 if region == "NC"
replace newwt = 1382/135 if region == "S"
replace newwt = 422/41 if region == "W"
gen total = acres92*newwt
tabstat total, s(sum) format(%15.0g)
variable | sum
-------------+----------
total | 909736007.481
------------------------