
Tests the homogeneity of proportions between
donner(formula = NULL, response = NULL,
weights = NULL, group = NULL, data, C = NULL)
An object of formal class “drs”: see drs-class
for details. The slot tab
provides the proportion of successes and the correction factor for each group.
An optional formula where the left-hand side is either a matrix of the form cbind(y, n-y)
, where
the modelled probability is y/n
, or a vector of proportions to be modelled (y/n
). In both cases, the
right-hand side must specify a single grouping variable. When the left-hand side of the formula is a vector of
proportions, the argument weight
must be used to indicate the denominators of the proportions.
An optional argument indicating either a matrix of the form cbind(y, n-y)
, where the modelled
probability is y/n
, or a vector of proportions to be modelled (y/n
).
An optional argument used when the left-hand side of formula
or response
is a vector
of proportions: weight
is the denominator of the proportion.
An optional argument only used when response
is used. In this case, this argument is a factor
indicating a grouping variable.
A data frame containing the response (n
and y
) and the grouping variable.
If not NULL, a numerical vector of
Matthieu Lesnoff matthieu.lesnoff@cirad.fr, Renaud Lancelot renaud.lancelot@cirad.fr
The C
.
Donner, A., 1989. Statistical methods in ophthalmology: an adjusted chi-squared approach. Biometrics 45, 605-611.
Donner, A., 1993. The comparison of proportions in the presence of litter effects. Prev. Vet. Med. 18, 17-26.
Donner, A., Eliasziw, M., Klar, N., 1994. A comparison of methods for testing homogeneity of proportions in
teratologic studies. Stat. Med. 13, 1253-1264.
chisq.test
, raoscott
, drs-class
data(rats)
donner(formula = cbind(y, n - y) ~ group, data = rats)
donner(formula = y/n ~ group, weights = n, data = rats)
donner(response = cbind(y, n - y), group = group, data = rats)
donner(response = y/n, weights = n, group = group, data = rats)
# standard test
donner(cbind(y, n - y) ~ group, data = rats, C = c(1, 1))
data(antibio)
donner(cbind(y, n - y) ~ treatment, data = antibio)
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