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First, I appoligise for the rooky question, but...
I'm trying to obtain standard errors, confidence intervals, etc. from a
sample design and have been trouble getting the results for anything other
than the basic total or mean for the overall survey from the survey
package.
For example, using the following dataset,
strata,cluster,vol
A,1,18.58556192
A,1,12.55175443
A,1,21.65882438
A,1,17.11172946
A,1,15.41713348
A,2,13.9344623
A,2,17.13104821
A,2,14.6806479
A,2,14.68357291
A,2,18.86017714
A,2,20.67642515
A,2,15.15295351
A,2,13.82121102
A,2,12.9110477
A,2,14.83153677
A,2,21.90772687
A,3,18.69795427
A,3,18.45636428
A,3,15.77175793
A,3,15.54715217
A,3,20.31948393
A,3,19.26391445
A,3,15.54750775
A,3,19.18724018
A,4,12.89572151
A,4,12.92047701
A,4,12.64958757
A,4,19.85888418
A,4,19.64057669
A,4,19.19188964
A,4,18.81619298
A,4,21.73670878
A,5,15.99430802
A,5,18.66666517
A,5,21.80441654
A,5,14.22081904
A,5,16.01576433
A,5,14.92497202
A,5,17.95123218
A,5,19.82027165
A,5,19.35698273
A,5,19.10826519
B,6,13.40892677
B,6,14.3956207
B,6,13.82113391
B,6,16.37338569
B,6,19.70159575
B,7,14.74334178
B,7,16.55125245
B,7,12.38329798
B,7,18.16472408
B,7,16.32938475
B,7,16.06465494
B,7,12.63086062
B,7,14.46114813
B,7,21.90134013
B,7,13.81025827
B,7,15.85805494
B,7,20.18195326
B,8,19.05120792
B,8,12.83856639
B,8,12.61360139
B,8,21.30434314
B,8,14.19960469
B,8,17.38397826
B,8,15.66477339
B,8,22.07182834
B,8,12.07487394
B,8,20.36357359
B,8,20.2543677
B,9,14.44499362
B,9,17.77235228
B,9,13.01620902
B,9,18.10976359
B,10,18.22350661
B,10,18.41504728
B,10,17.94735486
B,10,18.39173938
B,10,14.21729704
B,10,16.95753684
B,10,21.11643087
B,10,16.09688752
B,10,19.54707452
B,10,22.00450065
B,10,15.15308873
B,10,14.72488972
B,10,17.65280737
B,10,14.61615255
B,10,12.89525607
B,11,22.35831089
B,11,18.0853187
B,11,22.12815791
B,11,17.74562214
B,11,21.45724242
B,11,20.57933779
B,11,19.97397415
B,11,16.34967424
B,12,22.14385376
B,12,17.82816113
B,12,18.37056381
B,12,16.13152759
B,12,22.06764318
B,12,12.80924472
B,12,18.95522175
B,13,20.40554286
B,13,19.72951878
C,14,15.51581
C,14,15.4836358
C,14,13.35882363
C,14,13.16072916
C,14,21.69168971
C,14,19.09686303
C,14,14.47450457
C,14,12.04870424
C,14,13.33096141
C,14,17.38388981
C,14,16.29015289
C,14,16.32707754
C,14,16.2784054
C,15,15.0170597
C,15,14.95767365
C,15,15.20739614
C,15,22.10458509
C,15,12.3362457
C,15,19.87895753
C,15,18.8363682
C,15,16.43738666
C,15,12.84570744
C,15,15.99869357
C,15,14.42551321
C,15,13.63489872
C,15,15.67179885
C,16,14.61700901
C,16,14.64864676
C,16,14.13014582
C,16,21.7637441
C,16,20.66825543
C,16,17.05977818
C,16,17.80118916
C,16,15.16641698
where this is read into stand.data. When I use the following survey designs,
srv1 <- svydesign(ids=~1, strata=~strata, data=stand.data )
or,
srv1 <- svydesign(ids=~cluster, strata=~strata, data=stand.data )
with,
print( svytotal( ~vol, srv1 ) )
I only obtain the total,
> print( svytotal( ~vol, srv1 ) )
total SE
vol 2377 34.464
or worse,
print( svytotal( ~vol + strata, srv1 ) )
total SE
vol 2377.0 34.464
strataA 42.0 0.000
strataB 64.0 0.000
strataC 34.0 0.000
which reports the number of observations in each of the strata. I'm sure
this is a RTFM question, but I just need a start. The size of each "plot"
is 0.04 units (hectares) and I want to be able to quickly examine working
up each sample with and without clusters (this is going to be part of a
larger simulation study).
I'm trying to not use SAS for this and hate to admit defeat.
Thanks,
Jeff.
______________________________________________
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https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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Try the examples here:
?ftable.svystat
On 8/02/2006 12:23 p.m., Jeff D. Hamann wrote:
> First, I appoligise for the rooky question, but...
>
> I'm trying to obtain standard errors, confidence intervals, etc. from a
> sample design and have been trouble getting the results for anything other
> than the basic total or mean for the overall survey from the survey
> package.
>
> For example, using the following dataset,
>
> strata,cluster,vol
> A,1,18.58556192
> A,1,12.55175443
> A,1,21.65882438
> A,1,17.11172946
> A,1,15.41713348
> A,2,13.9344623
> A,2,17.13104821
> A,2,14.6806479
> A,2,14.68357291
> A,2,18.86017714
> A,2,20.67642515
> A,2,15.15295351
> A,2,13.82121102
> A,2,12.9110477
> A,2,14.83153677
> A,2,21.90772687
> A,3,18.69795427
> A,3,18.45636428
> A,3,15.77175793
> A,3,15.54715217
> A,3,20.31948393
> A,3,19.26391445
> A,3,15.54750775
> A,3,19.18724018
> A,4,12.89572151
> A,4,12.92047701
> A,4,12.64958757
> A,4,19.85888418
> A,4,19.64057669
> A,4,19.19188964
> A,4,18.81619298
> A,4,21.73670878
> A,5,15.99430802
> A,5,18.66666517
> A,5,21.80441654
> A,5,14.22081904
> A,5,16.01576433
> A,5,14.92497202
> A,5,17.95123218
> A,5,19.82027165
> A,5,19.35698273
> A,5,19.10826519
> B,6,13.40892677
> B,6,14.3956207
> B,6,13.82113391
> B,6,16.37338569
> B,6,19.70159575
> B,7,14.74334178
> B,7,16.55125245
> B,7,12.38329798
> B,7,18.16472408
> B,7,16.32938475
> B,7,16.06465494
> B,7,12.63086062
> B,7,14.46114813
> B,7,21.90134013
> B,7,13.81025827
> B,7,15.85805494
> B,7,20.18195326
> B,8,19.05120792
> B,8,12.83856639
> B,8,12.61360139
> B,8,21.30434314
> B,8,14.19960469
> B,8,17.38397826
> B,8,15.66477339
> B,8,22.07182834
> B,8,12.07487394
> B,8,20.36357359
> B,8,20.2543677
> B,9,14.44499362
> B,9,17.77235228
> B,9,13.01620902
> B,9,18.10976359
> B,10,18.22350661
> B,10,18.41504728
> B,10,17.94735486
> B,10,18.39173938
> B,10,14.21729704
> B,10,16.95753684
> B,10,21.11643087
> B,10,16.09688752
> B,10,19.54707452
> B,10,22.00450065
> B,10,15.15308873
> B,10,14.72488972
> B,10,17.65280737
> B,10,14.61615255
> B,10,12.89525607
> B,11,22.35831089
> B,11,18.0853187
> B,11,22.12815791
> B,11,17.74562214
> B,11,21.45724242
> B,11,20.57933779
> B,11,19.97397415
> B,11,16.34967424
> B,12,22.14385376
> B,12,17.82816113
> B,12,18.37056381
> B,12,16.13152759
> B,12,22.06764318
> B,12,12.80924472
> B,12,18.95522175
> B,13,20.40554286
> B,13,19.72951878
> C,14,15.51581
> C,14,15.4836358
> C,14,13.35882363
> C,14,13.16072916
> C,14,21.69168971
> C,14,19.09686303
> C,14,14.47450457
> C,14,12.04870424
> C,14,13.33096141
> C,14,17.38388981
> C,14,16.29015289
> C,14,16.32707754
> C,14,16.2784054
> C,15,15.0170597
> C,15,14.95767365
> C,15,15.20739614
> C,15,22.10458509
> C,15,12.3362457
> C,15,19.87895753
> C,15,18.8363682
> C,15,16.43738666
> C,15,12.84570744
> C,15,15.99869357
> C,15,14.42551321
> C,15,13.63489872
> C,15,15.67179885
> C,16,14.61700901
> C,16,14.64864676
> C,16,14.13014582
> C,16,21.7637441
> C,16,20.66825543
> C,16,17.05977818
> C,16,17.80118916
> C,16,15.16641698
>
> where this is read into stand.data. When I use the following survey designs,
>
> srv1 <- svydesign(ids=~1, strata=~strata, data=stand.data )
>
> or,
>
> srv1 <- svydesign(ids=~cluster, strata=~strata, data=stand.data )
>
> with,
>
> print( svytotal( ~vol, srv1 ) )
>
> I only obtain the total,
>
>> print( svytotal( ~vol, srv1 ) )
> total SE
> vol 2377 34.464
>
> or worse,
>
> print( svytotal( ~vol + strata, srv1 ) )
> total SE
> vol 2377.0 34.464
> strataA 42.0 0.000
> strataB 64.0 0.000
> strataC 34.0 0.000
>
> which reports the number of observations in each of the strata. I'm sure
> this is a RTFM question, but I just need a start. The size of each "plot"
> is 0.04 units (hectares) and I want to be able to quickly examine working
> up each sample with and without clusters (this is going to be part of a
> larger simulation study).
>
> I'm trying to not use SAS for this and hate to admit defeat.
>
> Thanks,
> Jeff.
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html--
James Reilly
Department of Statistics, University of Auckland
Private Bag 92019, Auckland, New Zealand
______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
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