cond.## S3 method for class 'cond':
summary(object, alpha = 0.05, test = NULL, all = FALSE, coef = TRUE,
int = ifelse( (is.null(test) || all), TRUE, FALSE),
digits = NULL, ...)cond object. This is assumed to be the result returned
by the cond.glm function.NULL, no test is performed. The default is
NULL.TRUE, all the information stored in the
summary.cond object is printed, else only a subset of it.
The default is FALSE.TRUE, the unconditional and conditional
parameter estimates are printed. The default is TRUE.TRUE confidence intervals are printed.
The default is TRUE.digits set by options.alpha, the
upper and lower confidence bounds derived from several first- and
higher order test statistics. One-sided and two-sided confidence
intervals are considered. See cond.object for
details on the test statistics.stats) contains, for
each value given in test, the values and tail probabilities
of several first- and higher order test statistics. See
cond.object for details on the test statistics.The
second element of the list (qTerm) contains for each tested
hypothesis the correction term used in the higher order solutions.cond object.cond.object for details.TRUE, all the information stored in the
summary.cond object is printed.TRUE, the unconditional and conditional
parameter estimates are printed.TRUE, confidence intervals are printed.FALSE there are none.summary()
for objects of class cond. It can be invoked by calling
summary or directly summary.cond for an object of the
appropriate class.summary, cond.object## Crying Babies Data
data(babies)
babies.glm <- glm(formula = cbind(r1, r2) ~ day + lull - 1,
family = binomial, data = babies)
babies.cond <- cond(object = babies.glm, offset = lullyes)
summary(babies.cond, test = 0, coef = FALSE)Run the code above in your browser using DataLab