Using Asthma Data with condGEE
David Clement
# data is available from: http://www.blackwellpublishing.com/rss/Volumes/Cv52p3.htm
# it was previously used by Duchateau et al. JRSSC volume 52 (2003), part 3, pages 355-363
library(condGEE)
data(asthma)
n.subjects <- length(unique(asthma$id.w))
med.nar <- 4 #median time not at risk before current gap
med.rec <- 40 #median length of at risk period
i <- 1
k <- 1
asth <- NULL
while(k <= n.subjects)
{
n <- asthma$nn[i] #number of gaps for subject k
inds <- i:(i+n-1) #indices of subject k's gaps
gaps <- asthma$stop.w[inds] - asthma$start.w[inds]
if(n > 1)
{
nar <- (asthma$start.w[inds[-1]]-asthma$stop.w[inds[-n]]) > med.nar
rec <- gaps[1:(n-1)] > med.rec
}
age1 <- asthma$start.w[inds]>182 & asthma$start.w[inds]<366
age2 <- asthma$start.w[inds]>=366
subj.k <- cbind(asthma$id.w[i], log(gaps), asthma$st.w[i:(i+n-1)], asthma$trt.w[i],
!asthma$fevent[i:(i+n-1)], c(0,nar), c(0,rec), asthma$trt.w[i]*c(0,nar),
age1, age2)
asth <- rbind(asth, subj.k)
k <- k + 1
i <- i + n
}
#the results look at little different than Clement and Strawderman (2009) because our code
#has been updated. Qualitatively nothing has changed though.
start <- c(4.4, 0.4, -1, 0.3, 0.8, -0.5, -0.3, -0.5, 3)
condGEE(asth, start, k1 = K1.t3, k2 = K2.t3)
## $eta
## [1] 4.4167117 0.4442439 -0.7225587 0.3222722 0.7167941 -0.4635109 -0.3159546
## [8] -0.4485230 3.3774312
##
## $a.var
## [,1] [,2] [,3] [,4] [,5]
## [1,] 0.0181177345 -0.016778062 -0.006772284 -0.0034127331 -0.002945423
## [2,] -0.0167780617 0.029670179 -0.007025685 0.0066486483 0.008040455
## [3,] -0.0067722836 -0.007025685 0.064219473 -0.0107144909 -0.034814486
## [4,] -0.0034127331 0.006648648 -0.010714491 0.0200782559 0.005566964
## [5,] -0.0029454226 0.008040455 -0.034814486 0.0055669643 0.039440200
## [6,] 0.0072011667 -0.011143623 -0.002277381 -0.0163149035 -0.005664269
## [7,] 0.0004249389 0.002806742 -0.019789443 0.0012410649 0.005481312
## [8,] -0.0015381352 0.005898135 -0.019638789 -0.0007288387 0.002682853
## [9,] -0.0074545630 0.005291254 -0.002729188 0.0019672451 0.008905041
## [,6] [,7] [,8] [,9]
## [1,] 0.0072011667 4.249389e-04 -0.0015381352 -7.454563e-03
## [2,] -0.0111436231 2.806742e-03 0.0058981345 5.291254e-03
## [3,] -0.0022773808 -1.978944e-02 -0.0196387889 -2.729188e-03
## [4,] -0.0163149035 1.241065e-03 -0.0007288387 1.967245e-03
## [5,] -0.0056642690 5.481312e-03 0.0026828532 8.905041e-03
## [6,] 0.0454385114 3.793633e-04 0.0070598181 9.920955e-04
## [7,] 0.0003793633 1.980044e-02 0.0130080867 7.656330e-06
## [8,] 0.0070598181 1.300809e-02 0.0251653582 -2.140584e-04
## [9,] 0.0009920955 7.656330e-06 -0.0002140584 3.771240e-02