Hello,
I need to run a multilevel analysis (on two levels) using Cox frailty survival model on a survey data. My problem is how to write the design weight using the two weights needed and apply them to the analysis.
I have identified the needed variables for the survey design, which are; psu/cluster=~v021, individual level-weight=~wt1_1, cluster level-weigh=~wt2_1 ,strata/stratum=~v022.
Please can someone help me with the svydesign code and how to include it and the weights in a model.
For instance, how do I account for the 2 weights in the gamma frailty model below?
Thank you for the anticipated help.
library(survey)
#> Warning: package 'survey' was built under R version 4.0.5
#> Loading required package: grid
#> Loading required package: Matrix
#> Loading required package: survival
#> Warning: package 'survival' was built under R version 4.0.5
#>
#> Attaching package: 'survey'
#> The following object is masked from 'package:graphics':
#>
#> dotchart
library(survival)
library(datapasta)
#> Warning: package 'datapasta' was built under R version 4.0.5
library(reprex)
#> Warning: package 'reprex' was built under R version 4.0.5
Model.frailty.gamma <- coxph (Surv(study_time, died) ~ factor(v024) + factor(mat_edu) + v025 + frailty(v021,distribution="gamma"), data=rcom2018)
#> Error in terms.formula(formula, specials = ss, data = data): object 'rcom2018' not found
datapasta::df_paste (head(rcom2018, 50)[, c('pid', 'study_time', 'died', 'v021', 'v022', 'v012', 'wt2_1', 'wt1_1', 'v024', 'v025', 'mat_edu')])
#> Error in h(simpleError(msg, call)): error in evaluating the argument 'x' in selecting a method for function 'head': object 'rcom2018' not found
data.frame(
pid = c(1,2,3,4,
5,6,7,8,9,10,11,12,13,14,15,16,17,
18,19,20,21,22,23,24,25,26,27,28,29,
30,31,32,33,34,35,36,37,38,39,40,
41,42,43,44,45,46,47,48,49,50),
study_time = c(13,9,17,
31,39,22,24,0,23,12,9,35,18,20,60,
18,5,46,26,54,37,51,31,55,27,15,39,6,
29,0,9,40,23,12,35,56,14,40,57,42,
5,42,39,39,54,19,52,42,7,28),
died = c(0,0,0,0,
0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0),
v021 = c(1,1,1,1,
1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,
2,2,2,2,2,2,2,2,2,2,2,2,2,2,3,
3,3,3,3,3,3,3,3,3,3,3,3,3,4,4),
v022 = c("1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1"),
v012 = c(40,37,27,
27,24,32,35,35,34,20,28,28,26,24,24,
25,26,26,26,26,28,27,25,25,27,26,
26,21,21,31,36,36,27,23,32,32,33,33,
33,28,25,37,33,34,33,28,28,29,33,33),
wt2_1 = c(401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031,
401.200012207031,401.200012207031,
401.200012207031,401.200012207031,401.200012207031),
wt1_1 = c(2.5074667930603,2.5074667930603,2.5074667930603,
2.5074667930603,2.5074667930603,2.5074667930603,
2.5074667930603,2.5074667930603,2.5074667930603,
2.5074667930603,2.5074667930603,
2.5074667930603,2.5074667930603,2.5074667930603,
2.5074667930603,5.1194109916687,5.1194109916687,
5.1194109916687,5.1194109916687,5.1194109916687,
5.1194109916687,5.1194109916687,
5.1194109916687,5.1194109916687,5.1194109916687,
5.1194109916687,5.1194109916687,5.1194109916687,
5.1194109916687,5.1194109916687,5.1194109916687,
5.1194109916687,5.1194109916687,
5.1194109916687,2.40910983085632,2.40910983085632,
2.40910983085632,2.40910983085632,2.40910983085632,
2.40910983085632,2.40910983085632,
2.40910983085632,2.40910983085632,2.40910983085632,
2.40910983085632,2.40910983085632,2.40910983085632,
2.40910983085632,1.06203985214233,
1.06203985214233),
v024 = c("1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1"),
v025 = c("1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1","1",
"1","1","1","1","1","1","1","1","1",
"1"),
mat_edu = c("5","5",
"5","4","4","5","4","4","4","4","4","4",
"5","5","5","5","5","5","4","4","5",
"4","4","4","5","3","3","4","4","5",
"5","5","5","4","2","2","0","0","0","5",
"5","0","1","5","5","3","3","5","5",
"5")
)
#> pid study_time died v021 v022 v012 wt2_1 wt1_1 v024 v025 mat_edu
#> 1 1 13 0 1 1 40 401.2 2.507467 1 1 5
#> 2 2 9 0 1 1 37 401.2 2.507467 1 1 5
#> 3 3 17 0 1 1 27 401.2 2.507467 1 1 5
#> 4 4 31 0 1 1 27 401.2 2.507467 1 1 4
#> 5 5 39 0 1 1 24 401.2 2.507467 1 1 4
#> 6 6 22 0 1 1 32 401.2 2.507467 1 1 5
#> 7 7 24 0 1 1 35 401.2 2.507467 1 1 4
#> 8 8 0 1 1 1 35 401.2 2.507467 1 1 4
#> 9 9 23 0 1 1 34 401.2 2.507467 1 1 4
#> 10 10 12 0 1 1 20 401.2 2.507467 1 1 4
#> 11 11 9 0 1 1 28 401.2 2.507467 1 1 4
#> 12 12 35 0 1 1 28 401.2 2.507467 1 1 4
#> 13 13 18 0 1 1 26 401.2 2.507467 1 1 5
#> 14 14 20 0 1 1 24 401.2 2.507467 1 1 5
#> 15 15 60 0 1 1 24 401.2 2.507467 1 1 5
#> 16 16 18 0 2 1 25 401.2 5.119411 1 1 5
#> 17 17 5 0 2 1 26 401.2 5.119411 1 1 5
#> 18 18 46 0 2 1 26 401.2 5.119411 1 1 5
#> 19 19 26 0 2 1 26 401.2 5.119411 1 1 4
#> 20 20 54 0 2 1 26 401.2 5.119411 1 1 4
#> 21 21 37 0 2 1 28 401.2 5.119411 1 1 5
#> 22 22 51 0 2 1 27 401.2 5.119411 1 1 4
#> 23 23 31 0 2 1 25 401.2 5.119411 1 1 4
#> 24 24 55 0 2 1 25 401.2 5.119411 1 1 4
#> 25 25 27 0 2 1 27 401.2 5.119411 1 1 5
#> 26 26 15 0 2 1 26 401.2 5.119411 1 1 3
#> 27 27 39 0 2 1 26 401.2 5.119411 1 1 3
#> 28 28 6 0 2 1 21 401.2 5.119411 1 1 4
#> 29 29 29 0 2 1 21 401.2 5.119411 1 1 4
#> 30 30 0 1 2 1 31 401.2 5.119411 1 1 5
#> 31 31 9 0 2 1 36 401.2 5.119411 1 1 5
#> 32 32 40 0 2 1 36 401.2 5.119411 1 1 5
#> 33 33 23 0 2 1 27 401.2 5.119411 1 1 5
#> 34 34 12 0 2 1 23 401.2 5.119411 1 1 4
#> 35 35 35 0 3 1 32 401.2 2.409110 1 1 2
#> 36 36 56 0 3 1 32 401.2 2.409110 1 1 2
#> 37 37 14 0 3 1 33 401.2 2.409110 1 1 0
#> 38 38 40 0 3 1 33 401.2 2.409110 1 1 0
#> 39 39 57 0 3 1 33 401.2 2.409110 1 1 0
#> 40 40 42 0 3 1 28 401.2 2.409110 1 1 5
#> 41 41 5 0 3 1 25 401.2 2.409110 1 1 5
#> 42 42 42 0 3 1 37 401.2 2.409110 1 1 0
#> 43 43 39 0 3 1 33 401.2 2.409110 1 1 1
#> 44 44 39 0 3 1 34 401.2 2.409110 1 1 5
#> 45 45 54 0 3 1 33 401.2 2.409110 1 1 5
#> 46 46 19 0 3 1 28 401.2 2.409110 1 1 3
#> 47 47 52 0 3 1 28 401.2 2.409110 1 1 3
#> 48 48 42 0 3 1 29 401.2 2.409110 1 1 5
#> 49 49 7 0 4 1 33 401.2 1.062040 1 1 5
#> 50 50 28 0 4 1 33 401.2 1.062040 1 1 5
Created on 2022-01-03 by the reprex package (v2.0.1)