The respdis data frame has 111 rows and 3 columns. The study
described in Miller et. al. (1993) is a randomized clinical trial of a
new treatment of respiratory disorder. The study was conducted in 111
patients who were randomly assigned to one of two treatments (active,
placebo). At each of four visits during the follow-up period, the
response status of each patients was classified on an ordinal scale.
Usage
data(respdis)
Format
This data frame contains the following columns:
y1, y2, y3, y4
ordered factor measured at 4 visits for
the response with levels, 1 < 2 < 3,
1 = poor, 2 = good, and 3 = excellent
trt
a factor for treatment with levels, 1 = active, 0 =
placebo.
References
Miller, M.E., David, C.S., and Landis, R.J. (1993) The analysis of
longitudinal polytomous data: Generalized estimating equation and
connections with weighted least squares, Biometrics49: 1033-1048.
Examples
data(respdis)
resp.l <- reshape(respdis, varying = list(c("y1", "y2", "y3", "y4")),
v.names = "resp", direction = "long")
resp.l <- resp.l[order(resp.l$id, resp.l$time),]
fit <- ordgee(ordered(resp) ~ trt, id = id, data = resp.l, int.const = FALSE)
summary(fit)
z <- model.matrix( ~ trt - 1, data = respdis)
ind <- rep(1:111, 4*3/2 * 2^2)
zmat <- z[ind,,drop=FALSE]
fit <- ordgee(ordered(resp) ~ trt, id = id, data = resp.l, int.const = FALSE,
z = zmat, corstr = "exchangeable")
summary(fit)