glm
s for binary data.
chisq_gof(x, prob = NULL, weights = NULL)
glm
-object.x
's amount of categories / factor levels. Use nrow(table(x))
to
determine the amount of necessary values for prob
. Only used,
when x
is a vector, and not a glm
-object.x
.chisq.test
.For glm
-objects, an object of class chisq_gof
with
following values:
p.value
the p-value for the goodness-of-fit test
z.score
the standardized z-score for the goodness-of-fit test
RSS
the residual sums of squares term
X2
the pearson chi-squared statistic
data(efc)
# differing from population
chisq_gof(efc$e42dep, c(0.3,0.2,0.22,0.28))
# equal to population
chisq_gof(efc$e42dep, prop.table(table(efc$e42dep)))
# goodness-of-fit test for logistic regression
efc$services <- ifelse(efc$tot_sc_e > 0, 1, 0)
fit <- glm(services ~ neg_c_7 + c161sex + e42dep, data = efc,
family = binomial(link = "logit"))
chisq_gof(fit)
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