summary.cond {cond} | R Documentation |
Returns a summary list for objects of class 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, ...)
object |
a cond object. This is assumed to be the result returned
by the cond.glm function.
|
alpha |
vector of levels for confidence intervals. The default is 5%. |
test |
vector of values of the parameter of interest one wants to test
for. If NULL , no test is performed. The default is
NULL .
|
all |
logical value; if TRUE , all the information stored in the
summary.cond object is printed, else only a subset of it.
The default is FALSE .
|
coef |
logical value; if TRUE , the unconditional and conditional
parameter estimates are printed. The default is TRUE .
|
int |
logical value; if TRUE confidence intervals are printed.
The default is TRUE .
|
digits |
number of significant digits to be printed. The default depends
on the value of digits set by options .
|
... |
absorbs any additional argument. |
This function is a method for the generic function summary()
for objects of class cond
. It can be invoked by calling
summary
or directly summary.cond
for an object of the
appropriate class.
A list is returned with the following components.
coefficients |
a 2x2 matrix containing the unconditional and approximate conditional MLEs and their standard errors. |
conf.int |
a matrix containing, for each level given in 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.
|
signif.tests |
a list with two elements. The first (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.
|
call |
the function call that created the cond object.
|
formula |
the model formula. |
family |
the variance function. |
offset |
the covariate occurring in the model formula whose coefficient represents the parameter of interest. |
alpha |
vector of levels used to compute the confidence intervals. |
hypotheses |
values for the parameter of interest that have been tested for. |
diagnostics |
information and nuisance parameters aspects; see
cond.object for details.
|
n.approx |
number of output points that have been calculated exactly. |
all |
logical value; if TRUE , all the information stored in the
summary.cond object is printed.
|
cf |
logical value; if TRUE , the unconditional and conditional
parameter estimates are printed.
|
int |
logical value; if TRUE , confidence intervals are printed.
|
is.scalar |
a logical value indicating whether there are any nuisance
parameters. If FALSE there are none.
|
digits |
number of significant digits to be printed. |
The amount of information calculated may vary depending on whether there are any nuisance parameters.
## 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)