Stata OUTPUT FOR EXEMPLAR 3

Stata commands in white, output in green and yellow, warnings are in red
Comments on interpretation of output are in blue.
For comments on running the analyses go to the commented code file.

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Setting up a survey design and getting SEs
Looking at the effect of alternative designs on precision
Subgroups and comparing groups
Looking at regional rates
Logistic regression
Using replication methods

. svyset [pwei=weighta],psu(psu) strata(regstrat)
pweight is weighta
strata is regstrat
psu is psu.
svydes
pweight:  weighta
Strata:   regstrat
PSU:      psu
#Obs per PSU
Strata                       ----------------------------
regstrat    #PSUs     #Obs       min      mean       max
--------  --------  --------  --------  --------  --------
101         2        48        23      24.0        25
102         2        45        21      22.5        24
103         2        58        18      29.0        40
104         2        65        26      32.5        39
105         2        52        24      26.0        28
lines cut out
717         2        38        16      19.0        22
718         2        57        24      28.5        33
719         2        51        24      25.5        27
--------  --------  --------  --------  --------  --------
154       312      9047        12      29.0        43

. svyprop cigst1

------------------------------------------------------------------------------
pweight:  weighta                               Number of obs      =      9047
Strata:   regstrat                              Number of strata   =       154
PSU:      psu                                   Number of PSUs     =       312
Population size    =  9006.178
------------------------------------------------------------------------------

Survey proportions estimation

+-----------------------------------------------------------------------+
|                                cigst1    Obs   Est. Prop.   Std. Err. |
|-----------------------------------------------------------------------|
|                  Refused/Not answered     14     0.001534    0.000491 |
|                             Dont know     16     0.002548    0.000716 |
|                 schedule not obtained      3     0.000601    0.000371 |
|                        not applicable      3     0.000230    0.000133 |
|        Never smoked cigarettes at all   3711     0.436668    0.006127 |
|-----------------------------------------------------------------------|
| Used to smoke cigarettes occasionally    269     0.030702    0.002425 |
|    Used to smoke cigarettes regularly   1895     0.196159    0.004592 |
|              Current cigarette smoker   3136     0.331559    0.005967 |
+-----------------------------------------------------------------------+

. recode cigst1 (-9 -8 -6 =.) (-1 1 2 3=0) (4=1),gen(smoker)
. svymean smoker,deff deft ci

Survey mean estimation

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean |   Estimate    Std. Err.   [95% Conf. Interval]        Deff
---------+--------------------------------------------------------------------
smoker |   .3331194    .0060102    .3212486    .3449902    1.465561
------------------------------------------------------------------------------

------------------------------------------------------------------------------
Mean |       Deft
---------+--------------------------------------------------------------------
smoker |   1.210604
------------------------------------------------------------------------------

The next set of results look at results on design effects etc of ignoring
design features first just weights

. svyset, clear(all)
no variables are set

. svyset [pwei=weighta]
pweight is weighta

.  svymean smoker,deff deft

Survey mean estimation

pweight:  weighta                                 Number of obs   =      9014
Strata:                                          Number of strata =         1
PSU:                                             Number of PSUs   =      9014
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean |   Estimate    Std. Err.       Deff        Deft
---------+--------------------------------------------------------------------
smoker |   .3331194    .0057008    1.318523     1.14827
------------------------------------------------------------------------------

DE is just a bit >1 from weighting - now add strata

. svyset, clear(all)
no variables are set

. svyset [pwei=weighta],strata(regstrat)
pweight is weighta
strata is regstrat

.  svymean smoker,deff deft

Survey mean estimation

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:                                Number of PSUs   =      9014
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean |   Estimate    Std. Err.       Deff        Deft
---------+--------------------------------------------------------------------
smoker |   .3331194    .0056322    1.286988    1.134455
------------------------------------------------------------------------------
Improves things only a little -now psus no strata

. svyset, clear(all)
no variables are set

. svyset [pwei=weighta],psu(psu)
pweight is weighta
psu is psu

.  svymean smoker,deff deft

Survey mean estimation

pweight:  weighta                                 Number of obs    =      9014
Strata:                                      Number of strata =         1
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean |   Estimate    Std. Err.       Deff        Deft
---------+--------------------------------------------------------------------
smoker |   .3331194    .0074961    2.279774    1.509892
------------------------------------------------------------------------------

This shows that it is the PSUs that are the main reason for reduced precision
. svyset, clear(all)
no variables are set
Now the effect of subgroups and comparisons between groups
first go back to the original design
. svyset [pwei=weighta],strata(regstrat) psu(psu)
pweight is weighta
strata is regstrat
psu is psu
.
> now looking at rates by sex
. svymean smoker, by(sex)

Survey mean estimation

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean   Subpop. |   Estimate    Std. Err.   [95% Conf. Interval]        Deff
---------------+--------------------------------------------------------------
smoker         |
male |   .3419507    .0084952    .3251718    .3587296    1.419651
female |   .3245964    .0078806    .3090315    .3401614     1.29928
------------------------------------------------------------------------------

to get a test of differrences by sex use lincom
for linear combinations
. lincom [smoker]male-[smoker]female

( 1)  [smoker]male - [smoker]female = 0

------------------------------------------------------------------------------
Mean |   Estimate   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) |   .0173543   .0111258     1.56   0.121    -.0046203    .0393288
------------------------------------------------------------------------------

> and by adults in the household

Survey mean estimation

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean   Subpop. |   Estimate    Std. Err.   [95% Conf. Interval]        Deff
---------------+--------------------------------------------------------------
smoker         |
nofad==1 |   .4408193    .0099747    .4211183    .4605202    .6521785
nofad==2 |   .3189418    .0073425    .3044398    .3334438    1.219789
nofad==3 |   .2887937    .0145437    .2600685    .3175188    1.607311
nofad==4 |   .2894893    .0283638    .2334682    .3455104    2.801671
nofad==5 |   .3479849    .0740851    .2016601    .4943097    3.931923
nofad==6 |          0           0           0           0           .
nofad==7 |          0           0           0           0           .
nofad==8 |    .617777    .3339362   -.0417778    1.277332    6.100542
nofad==9 |          0           0           0           0           .
------------------------------------------------------------------------------

. lincom [smoker]1-[smoker]2

( 1)  [smoker]1 - [smoker]2 = 0

------------------------------------------------------------------------------
Mean |   Estimate   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) |   .1218775    .012969     9.40   0.000     .0962625    .1474925
------------------------------------------------------------------------------
. /*-------------------------------------------------
> smoking rates by region or health board are also easily calculated
> and lincom can give the comparisons between any pair
> or other combination
>
> -------------------------------------------------------*/
. svymean smoker, by(region)

Survey mean estimation

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean   Subpop. |   Estimate    Std. Err.   [95% Conf. Interval]        Deff
---------------+--------------------------------------------------------------
smoker         |
Highland |   .3278274    .0250704    .2783111    .3773436    1.375797
Grampian |   .3267013    .0160343     .295032    .3583705    1.900358
Lothian_ |   .3213779    .0114178    .2988266    .3439292    1.198679
Borders, |   .2893518    .0228964    .2441293    .3345743    1.128549
Glagow |   .3633258    .0164955    .3307457     .395906    1.845421
Lanarksh |   .3425938    .0131008    .3167184    .3684691    1.256116
Forth_Va |   .3273929    .0154412     .296895    .3578907    1.342229
------------------------------------------------------------------------------

. svymean smoker, by(hboard)

Survey mean estimation

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037

------------------------------------------------------------------------------
Mean   Subpop. |   Estimate    Std. Err.   [95% Conf. Interval]        Deff
---------------+--------------------------------------------------------------
smoker         |
Ayreshir |   .3405227    .0249012    .2913406    .3897047    2.091303
Borders |   .2751782    .0339687    .2080869    .3422696    1.216756
Argyll_& |   .3377994    .0226662    .2930315    .3825673    1.405142
Fife |   .3514359    .0179934    .3158974    .3869745    1.048564
Greater_ |   .3633258    .0164955    .3307457     .395906    1.845421
Highland |   .3594827    .0311305    .2979971    .4209684    1.563275
Lanarksh |   .3443544    .0187207    .3073794    .3813295    1.382976
Grampian |   .2982887    .0189685    .2608242    .3357531    1.442587
Orkney |   .2323456    .0107839    .2110463    .2536448    .0225086
Lothian |   .3038667    .0152057    .2738341    .3338993       1.385
Tayside |   .3570112     .024537    .3085483    .4054741    2.063279
Forth_Va |    .317252    .0228504    .2721205    .3623836    1.513442
Western_ |   .2505246    .0263358     .198509    .3025402    .1420666
Dumfries |   .3021828    .0269545    .2489452    .3554204    .8004963
Shetland |   .1831689    .0670901    .0506597    .3156781    1.141379
------------------------------------------------------------------------------

.
. lincom [smoker]Fife-[smoker]Lothian

( 1)  [smoker]Fife - [smoker]Lothian = 0

------------------------------------------------------------------------------
Mean |   Estimate   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) |   .0475692   .0237606     2.00   0.047     .0006399    .0944985
------------------------------------------------------------------------------

. lincom [smoker]Lanarksh-[smoker]Ayreshir

( 1) - [smoker]Ayreshir + [smoker]Lanarksh = 0

------------------------------------------------------------------------------
Mean |   Estimate   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
(1) |   .0038318   .0349296     0.11   0.913    -.0651573    .0728209
------------------------------------------------------------------------------
.
. /*--------- spelling mistake was in original file-----*/
. /*-----------------------------------------------------
> now logistic regressions to predict smoking
>
> To use categorical variables you must first generate a set of dummy variables
> here for number of adults
> --------------------------------------------------*/

Number of |
------------+-----------------------------------
1 |      3,046       33.67       33.67
2 |      4,613       50.99       84.66
3 |        992       10.96       95.62
4 |        330        3.65       99.27
5 |         56        0.62       99.89
6 |          6        0.07       99.96
7 |          1        0.01       99.97
8 |          2        0.02       99.99
9 |          1        0.01      100.00
------------+-----------------------------------
Total |      9,047      100.00

. /*----------------------------------------------
> check the data set to see the new variables
> as there are so few households of more than 5
> it seems sensible to group them together
> and then to carry out the regression
> ---------------------------------------------------*/

. /*---regressions include the comparisons with nofad1 only--------*/

Survey logistic regression

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037
F(   3,    156)  =     25.41
Prob > F         =    0.0000

------------------------------------------------------------------------------
smoker |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nofad2 |  -.4625912   .0598125    -7.73   0.000    -.5807264   -.3444561
nofad3 |  -.6052021   .0829158    -7.30   0.000    -.7689683   -.4414358
nofad4 |  -.6018177    .147868    -4.07   0.000    -.8938706   -.3097647
_cons |   -.296048   .0465228    -6.36   0.000    -.3879349   -.2041611
------------------------------------------------------------------------------

. /*------------ we can compare with simple logistic regression---------
> --------------use coef to get comaparable results to the svy command----*/

Logistic regression                               Number of obs   =       9014
LR chi2(3)      =     143.44
Prob > chi2     =     0.0000
Log likelihood =  -5752.579                       Pseudo R2       =     0.0123

------------------------------------------------------------------------------
smoker |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nofad2 |  -.5172813   .0482623   -10.72   0.000    -.6118737   -.4226889
nofad3 |  -.6473839   .0795895    -8.13   0.000    -.8033764   -.4913914
nofad4 |  -.6380871   .1279033    -4.99   0.000    -.8887729   -.3874012
_cons |  -.2803519   .0362628    -7.73   0.000    -.3514257   -.2092781
------------------------------------------------------------------------------

. /*-------------- and we can get more complicated models
>                  looking at joint effect of age group sex
> Test commands can be used to check if variables are significant in
>  the larger models
> --------------------------------------------------------------*/
. tabulate hboard,generate(hboard)

Health Board |      Freq.     Percent        Cum.
--------------------+-----------------------------------
Ayreshire & Arran |        744        8.22        8.22
Borders |        388        4.29       12.51
Argyll & Clyde |        614        6.79       19.30
Fife |        662        7.32       26.62
Greater Glasgow |      1,294       14.30       40.92
Highland |        681        7.53       48.45
Lanarkshire |        871        9.63       58.07
Grampian |        726        8.02       66.10
Orkney |         63        0.70       66.80
Lothian |      1,174       12.98       79.77
Tayside |        725        8.01       87.79
Forth Valley |        509        5.63       93.41
Western Isles |         98        1.08       94.50
Dumfries & Galloway |        438        4.84       99.34
Shetland |         60        0.66      100.00
--------------------+-----------------------------------
Total |      9,047      100.00

. tabulate ageg,generate(ageg)

ageg |      Freq.     Percent        Cum.
------------+-----------------------------------
16-19 |        391        4.32        4.32
25-29 |        536        5.92       10.25
35-39 |        765        8.46       18.70
45-49 |        973       10.75       29.46
55-59 |        984       10.88       40.33
65-69 |        852        9.42       49.75
70-74 |        759        8.39       58.14
60-64 |        831        9.19       67.33
50-54 |        742        8.20       75.53
40-44 |        750        8.29       83.82
30-34 |        760        8.40       92.22
20-24 |        704        7.78      100.00
------------+-----------------------------------
Total |      9,047      100.00

. tabulate sex,generate(sex)

Sex of |
respondent |
from |
household |
grid. O |      Freq.     Percent        Cum.
------------+-----------------------------------
male |      3,941       43.56       43.56
female |      5,106       56.44      100.00
------------+-----------------------------------
Total |      9,047      100.00

Survey logistic regression

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037
F(   3,    156)  =     25.41
Prob > F         =    0.0000

------------------------------------------------------------------------------
smoker |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nofad2 |  -.4625912   .0598125    -7.73   0.000    -.5807264   -.3444561
nofad3 |  -.6052021   .0829158    -7.30   0.000    -.7689683   -.4414358
nofad4 |  -.6018177    .147868    -4.07   0.000    -.8938706   -.3097647
_cons |   -.296048   .0465228    -6.36   0.000    -.3879349   -.2041611
------------------------------------------------------------------------------

Survey logistic regression

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037
F(  29,    130)  =     11.94
Prob > F         =    0.0000

------------------------------------------------------------------------------
smoker |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nofad2 |  -.5612387   .0609933    -9.20   0.000     -.681706   -.4407714
nofad3 |  -.7485357   .0909213    -8.23   0.000    -.9281135   -.5689578
nofad4 |  -.7860213   .1571321    -5.00   0.000    -1.096372    -.475671
sex2 |  -.1193292   .0521901    -2.29   0.024    -.2224095   -.0162489
ageg2 |   .4888972   .1821246     2.68   0.008     .1291843    .8486101
ageg3 |   .2063644   .1559656     1.32   0.188    -.1016821    .5144109
ageg4 |   .3205004   .1600491     2.00   0.047     .0043888    .6366121
ageg5 |   .1117259   .1457159     0.77   0.444    -.1760764    .3995282
ageg6 |   .2468631   .1576949     1.57   0.119     -.064599    .5583251
ageg7 |   .1650847   .1686705     0.98   0.329    -.1680551    .4982244
ageg8 |   .1918504   .1501647     1.28   0.203    -.1047388    .4884395
ageg9 |   .1454189   .1645114     0.88   0.378    -.1795063    .4703441
ageg10 |  -.1560555   .1598613    -0.98   0.330    -.4717963    .1596854
ageg11 |  -.4393657   .1757703    -2.50   0.013    -.7865283   -.0922032
ageg12 |  -.7704922   .1644425    -4.69   0.000    -1.095281   -.4457032
hboard2 |  -.2949776    .203661    -1.45   0.149    -.6972269    .1072717
hboard3 |  -.0308084    .145793    -0.21   0.833     -.318763    .2571462
hboard4 |    .017459   .1351148     0.13   0.897    -.2494052    .2843233
hboard5 |   .0521162   .1321553     0.39   0.694    -.2089026    .3131351
hboard6 |   .0988347   .1723596     0.57   0.567    -.2415914    .4392609
hboard7 |   .0257908   .1519292     0.17   0.865    -.2742833    .3258648
hboard8 |  -.2064544   .1482992    -1.39   0.166    -.4993589    .0864502
hboard9 |  -.5131615   .1361878    -3.77   0.000    -.7821449   -.2441781
hboard10 |  -.2055899   .1291238    -1.59   0.113    -.4606214    .0494415
hboard11 |   .0477432   .1538141     0.31   0.757    -.2560537    .3515401
hboard12 |  -.1433606   .1576678    -0.91   0.365    -.4547691    .1680478
hboard13 |  -.4630294   .1779328    -2.60   0.010     -.814463   -.1115958
hboard14 |  -.1637861   .1662252    -0.99   0.326    -.4920962     .164524
hboard15 |  -.8051732   .4804435    -1.68   0.096    -1.754093    .1437469
_cons |   -.196425   .1790967    -1.10   0.274    -.5501576    .1573076
------------------------------------------------------------------------------

. test sex2

( 1)  sex2 = 0

F(  1,   158) =    5.23
Prob > F =    0.0236

. test ageg2 ageg3 ageg4 ageg5 ageg6 ageg7 ageg8 ageg9 ageg10 ageg11 ageg12

( 1)  ageg2 = 0
( 2)  ageg3 = 0
( 3)  ageg4 = 0
( 4)  ageg5 = 0
( 5)  ageg6 = 0
( 6)  ageg7 = 0
( 7)  ageg8 = 0
( 8)  ageg9 = 0
( 9)  ageg10 = 0
(10)  ageg11 = 0
(11)  ageg12 = 0

F( 11,   148) =   13.25
Prob > F =    0.0000

. /*-----------------------------------------------------------------
> get dummies for the age sex interaction
> --------------------------------------------------------------------*/
. generate ageg2s=ageg2*(sex==1)

. generate ageg3s=ageg3*(sex==1)

. generate ageg4s=ageg4*(sex==1)

. generate ageg5s=ageg5*(sex==1)

. generate ageg6s=ageg6*(sex==1)

. generate ageg7s=ageg7*(sex==1)

. generate ageg8s=ageg8*(sex==1)

. generate ageg9s=ageg9*(sex==1)

. generate ageg10s=ageg10*(sex==1)

. generate ageg11s=ageg11*(sex==1)

. generate ageg12s=ageg12*(sex==1)

Survey logistic regression

pweight:  weighta                                 Number of obs    =      9014
Strata:   regstrat                                Number of strata =       154
PSU:      psu                                     Number of PSUs   =       312
Population size  = 8964.0037
F(  40,    119)  =      7.71
Prob > F         =    0.0000

------------------------------------------------------------------------------
smoker |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
nofad2 |  -.5649544   .0608856    -9.28   0.000    -.6852091   -.4446997
nofad3 |  -.7536616   .0926128    -8.14   0.000    -.9365805   -.5707427
nofad4 |  -.8098296   .1577345    -5.13   0.000     -1.12137   -.4982894
sex2 |   .2744983   .2710147     1.01   0.313    -.2607807    .8097773
ageg2 |   .0620744   .2462163     0.25   0.801    -.4242254    .5483743
ageg3 |   .0229399   .2295454     0.10   0.921    -.4304334    .4763131
ageg4 |  -.0247639   .2006926    -0.12   0.902    -.4211503    .3716225
ageg5 |  -.1542414   .1982643    -0.78   0.438    -.5458315    .2373488
ageg6 |   .0865896   .2108846     0.41   0.682    -.3299268    .5031061
ageg7 |  -.0092496    .224278    -0.04   0.967    -.4522192    .4337201
ageg8 |   .0533689   .1981527     0.27   0.788    -.3380009    .4447388
ageg9 |   .1510162   .2365119     0.64   0.524    -.3161166     .618149
ageg10 |  -.5590369   .2192275    -2.55   0.012    -.9920313   -.1260425
ageg11 |  -.5204729   .2332741    -2.23   0.027    -.9812107   -.0597351
ageg12 |  -.8953448   .2270752    -3.94   0.000    -1.343839   -.4468504
hboard2 |  -.3028365    .207801    -1.46   0.147    -.7132627    .1075896
hboard3 |  -.0337248   .1478331    -0.23   0.820    -.3257087    .2582592
hboard4 |   .0032226   .1385716     0.02   0.981    -.2704691    .2769143
hboard5 |   .0453948   .1320654     0.34   0.732    -.2154465     .306236
hboard6 |   .0938063   .1739568     0.54   0.590    -.2497744     .437387
hboard7 |   .0224807   .1529716     0.15   0.883    -.2796522    .3246136
hboard8 |  -.2122447   .1511458    -1.40   0.162    -.5107715    .0862821
hboard9 |  -.5275344   .1574306    -3.35   0.001    -.8384743   -.2165945
hboard10 |  -.2124226   .1302862    -1.63   0.105    -.4697497    .0449046
hboard11 |   .0445227   .1562242     0.28   0.776    -.2640345      .35308
hboard12 |  -.1588901   .1584109    -1.00   0.317    -.4717662     .153986
hboard13 |  -.4628882   .1811377    -2.56   0.012    -.8206519   -.1051246
hboard14 |  -.1826604   .1682906    -1.09   0.279    -.5150499    .1497291
hboard15 |  -.8062307   .4707845    -1.71   0.089    -1.736073    .1236121
ageg2s |    .824665   .3715844     2.22   0.028     .0907517    1.558578
ageg3s |   .3504848   .3230779     1.08   0.280    -.2876237    .9885933
ageg4s |   .6673566   .2912065     2.29   0.023      .092197    1.242516
ageg5s |   .5117199   .2978448     1.72   0.088     -.076551    1.099991
ageg6s |   .3084944   .3122679     0.99   0.325    -.3082634    .9252521
ageg7s |   .3364531   .3147512     1.07   0.287    -.2852094    .9581156
ageg8s |   .2614396   .3404926     0.77   0.444    -.4110647    .9339438
ageg9s |  -.0546145   .3289639    -0.17   0.868    -.7043484    .5951195
ageg10s |   .7881987   .3413227     2.31   0.022      .114055    1.462342
ageg11s |   .1063126   .3237929     0.33   0.743    -.5332082    .7458333
ageg12s |   .1880666   .3350127     0.56   0.575    -.4736143    .8497476
_cons |  -.3746603   .2330058    -1.61   0.110    -.8348683    .0855476
------------------------------------------------------------------------------

. test ageg2s ageg3s ageg4s ageg5s ageg6s ageg7s ageg8s ageg9s ageg10s ageg11s ageg12s

( 1)  ageg2s = 0
( 2)  ageg3s = 0
( 3)  ageg4s = 0
( 4)  ageg5s = 0
( 5)  ageg6s = 0
( 6)  ageg7s = 0
( 7)  ageg8s = 0
( 8)  ageg9s = 0
( 9)  ageg10s = 0
(10)  ageg11s = 0
(11)  ageg12s = 0

F( 11,   148) =    2.02
Prob > F =    0.0303

.
various steps need to be taken to set up for replication methods
memory needs to be increased and total for the population need to be attached to each record
details are in the code file output from these are not shown

post-stratified
we get the totals by adding the weights up from
the data file, since they have already been ste to match the population

you now have a file with agesex and region totals
now make a set of jacknife weights for this survey

. survwgt create jkn, psu(psu) weight(weight) strata(regstrat)
Generating replicate weights......................................................................................
> ................................................................................................................
> ................................................................................................................
> ..
Created weights and set svr values:
meth jkn
pw weighta
rw jkn_1 jkn_2 jkn_3 jkn_4 jkn_5 jkn_6 jkn_7 jkn_8 jkn_9 jkn_10 jkn_11 jkn_12 jkn_13 jkn_14 jkn_15 jkn_16
jkn_17 jkn_18 jkn_19 jkn_20 jkn_21 jkn_22 jkn_23 jkn_24 jkn_25 jkn_26 jkn_27 jkn_28 jkn_29 jkn_30 jkn_31
jkn_32 jkn_33 jkn_34 jkn_35 jkn_36 jkn_37 jkn_38 jkn_39 jkn_40 jkn_41 jkn_42 jkn_43 jkn_44 jkn_45 jkn_46

lines missed
jkn_276 jkn_277 jkn_278 jkn_279 jkn_280 jkn_281 jkn_282 jkn_283 jkn_284 jkn_285 jkn_286 jkn_287
jkn_288 jkn_289 jkn_290 jkn_291 jkn_292 jkn_293 jkn_294 jkn_295 jkn_296 jkn_297 jkn_298 jkn_299 jkn_300
jkn_301 jkn_302 jkn_303 jkn_304 jkn_305 jkn_306 jkn_307 jkn_308 jkn_309 jkn_310 jkn_311 jkn_312
dof 158
now use the survey replication commands first raking the original weight and
all the jackknife weights
This which does not change the weights for the main weight here, since they totals match already
but it does change the kacknife weights becasue they don't match
. survwgt rake [all] , by(agesex region) totvars( asext rtot) replace

SVR settings updated:
pw weighta
rw jkn_1 jkn_2 jkn_3 jkn_4 jkn_5 jkn_6 jkn_7 jkn_8 jkn_9 jkn_10 jkn_11 jkn_12 jkn_13 jkn_14 jkn_15 jkn_16
jkn_17 jkn_18 jkn_19 jkn_20 jkn_21 jkn_22 jkn_23 jkn_24 jkn_25 jkn_26 jkn_27 jkn_28 jkn_29 jkn_30 jkn_31
lines missed out
jkn_275 jkn_276 jkn_277 jkn_278 jkn_279 jkn_280 jkn_281 jkn_282 jkn_283 jkn_284 jkn_285 jkn_286 jkn_287
jkn_288 jkn_289 jkn_290 jkn_291 jkn_292 jkn_293 jkn_294 jkn_295 jkn_296 jkn_297 jkn_298 jkn_299 jkn_300
jkn_301 jkn_302 jkn_303 jkn_304 jkn_305 jkn_306 jkn_307 jkn_308 jkn_309 jkn_310 jkn_311 jkn_312

. save ex3reps,replace
file ex3reps.dta saved

> now use the replicate mean command to get the mean and design effect
> for smokers using a jacknife method
. svrmean smoker

Survey mean estimation, replication (jkn) variance method

Analysis weight:      weighta                  Number of obs       =      9014
Replicate weights:    jkn_1...                 Population size     = 8964.0037
Number of replicates: 312                      Degrees of freedom  =       158

------------------------------------------------------------------------------
Mean |   Estimate    Std. Err.   [95% Conf. Interval]        Deff
---------+--------------------------------------------------------------------
smoker |   .3331194    .0059549     .321358    .3448808    1.438681
------------------------------------------------------------------------------

After all that trouble we find it makes almost no difference. The original design effect was 1.465

```