Description Usage Format Examples

BiRepeated is a simulated data set with bi-Beta variables y1 and y2 on 200 independent cases. Both y1 and y2 are repeatedly measured at a given set of covariate values x = (0.1, 0.2, 0.3, 0.4, 0.5, 0.6). Joint zoib modeling is applied to examine the effect of x on y1 and y2 simultaneously.

1 |

A data frame with 200 independent cases, from which 6 measurements are taken on 2 response variables.

`id`

id of the 200 cases.

`y1`

value of one beta variable (6 measurements per case) ranged from 0 to 1.

`y2`

value of the other beta variables (6 measurements per case) ranged from 0 to 1.

`x`

numerical; explanatory variable.

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 | ```
## Not run:
library(zoib)
data("BiRepeated", package = "zoib")
eg2 <- zoib(y1|y2 ~ x|1|x, data= BiRepeated, random=1,n.response=2,
EUID= BiRepeated$id, joint=TRUE,zero.inflation = FALSE,
one.inflation = FALSE, prior.Sigma = "VC.unif",
n.iter=7000,n.thin=25,n.burn=2000)
coeff <- eg2$coeff
summary(coeff)
### check convergence
traceplot(coeff);
autocorr.plot(coeff);
check.psrf(coeff)
### plot posterior mean of y vs. observed y to check on goodness of fit.
n= nrow(BiRepeated)
ypred1 = rbind(eg2$ypred[[1]][,1:n],eg2$ypred[[2]][,1:n])
ypred2 = rbind(eg2$ypred[[1]][,(n+1):(2*n)],eg2$ypred[[2]][,(n+1):(2*n)])
post.mean1 = apply(ypred1,2,mean);
post.mean2 = apply(ypred2,2,mean);
plot(BiRepeated$y1, post.mean1, xlim=c(0,1),ylim=c(0,1), col='green2',
pch=2,xlab='Observed y', ylab='Predicted y', main="")
points(BiRepeated$y2,post.mean2,col='purple')
abline(0,1,col='red')
legend(0.1,0.9,col=c('green2','purple'),c("y1","y2"),pch=c(2,1))
## End(Not run)
``` |

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