Construct zcor vector

Construct zcor vector (of fixed correlations) from a fixed working correlation matrix, a specification of clusters and a specifcation of waves.

fixed2Zcor(cor.fixed, id, waves)

Arguments

cor.fixed

Matrix

id

Clusters

waves

Vector giving the ordering of observations within clusters.

Value

A vector which can be passed as the zcor argument to geeglm.

See also

genZcor, geeglm

Author

Søren Højsgaard, sorenh@math.aau.dk

Examples

timeorder <- rep(1:5, 6)
tvar      <- timeorder + rnorm(length(timeorder))
idvar <- rep(1:6, each=5)
uuu   <- rep(rnorm(6), each=5)
yvar  <- 1 + 2*tvar + uuu + rnorm(length(tvar))
simdat <- data.frame(idvar, timeorder, tvar, yvar)
head(simdat,12)
#>    idvar timeorder     tvar      yvar
#> 1      1         1 1.334497  3.020713
#> 2      1         2 1.170648  3.655398
#> 3      1         3 2.781304  4.436412
#> 4      1         4 2.454916  3.719308
#> 5      1         5 5.233230 11.779785
#> 6      2         1 1.031070  4.263892
#> 7      2         2 2.357866  5.327582
#> 8      2         3 4.608624 11.551966
#> 9      2         4 5.429854 13.232432
#> 10     2         5 4.051660  8.179241
#> 11     3         1 2.015706  4.878890
#> 12     3         2 2.037735  5.099036

simdatPerm <- simdat[sample(nrow(simdat)),]
simdatPerm <- simdatPerm[order(simdatPerm$idvar),]
head(simdatPerm)
#>    idvar timeorder     tvar      yvar
#> 5      1         5 5.233230 11.779785
#> 2      1         2 1.170648  3.655398
#> 1      1         1 1.334497  3.020713
#> 4      1         4 2.454916  3.719308
#> 3      1         3 2.781304  4.436412
#> 10     2         5 4.051660  8.179241

cor.fixed <- matrix(c(1    , 0.5  , 0.25,  0.125, 0.125,
                      0.5  , 1    , 0.25,  0.125, 0.125,
                      0.25 , 0.25 , 1   ,  0.5  , 0.125,
                      0.125, 0.125, 0.5  , 1    , 0.125,
                      0.125, 0.125, 0.125, 0.125, 1     ), nrow=5, ncol=5)
cor.fixed
#>       [,1]  [,2]  [,3]  [,4]  [,5]
#> [1,] 1.000 0.500 0.250 0.125 0.125
#> [2,] 0.500 1.000 0.250 0.125 0.125
#> [3,] 0.250 0.250 1.000 0.500 0.125
#> [4,] 0.125 0.125 0.500 1.000 0.125
#> [5,] 0.125 0.125 0.125 0.125 1.000

zcor <- fixed2Zcor(cor.fixed, id=simdatPerm$idvar, waves=simdatPerm$timeorder)
zcor
#>  [1] 0.125 0.125 0.125 0.125 0.500 0.125 0.250 0.125 0.250 0.500 0.125 0.125
#> [13] 0.125 0.125 0.500 0.250 0.125 0.250 0.125 0.500 0.125 0.125 0.125 0.500
#> [25] 0.125 0.500 0.250 0.125 0.125 0.250 0.125 0.125 0.250 0.500 0.125 0.500
#> [37] 0.125 0.125 0.125 0.250 0.250 0.250 0.125 0.500 0.500 0.125 0.125 0.125
#> [49] 0.125 0.125 0.125 0.125 0.500 0.250 0.125 0.125 0.125 0.125 0.500 0.250

mod4 <- geeglm(yvar~tvar, id=idvar, data=simdatPerm, corstr="fixed", zcor=zcor)
mod4
#> 
#> Call:
#> geeglm(formula = yvar ~ tvar, data = simdatPerm, id = idvar, 
#>     zcor = zcor, corstr = "fixed")
#> 
#> Coefficients:
#> (Intercept)        tvar 
#>    1.048262    1.969850 
#> 
#> Degrees of Freedom: 30 Total (i.e. Null);  28 Residual
#> 
#> Scale Link:                   identity
#> Estimated Scale Parameters:  [1] 1.523422
#> 
#> Correlation:  Structure = fixed    Link = identity 
#> Estimated Correlation Parameters:
#> alpha:1 
#>       1 
#> 
#> Number of clusters:   6   Maximum cluster size: 5 
#>