Nothing
tol <- 1e-4
backPainLong <- expandCategorical(backPain, "pain")
## stereotype model
stereotype <- gnm(count ~ pain + Mult(pain, x1 + x2 + x3),
eliminate = id, family = "poisson",
data = backPainLong, verbose = FALSE)
test_that("sterotype model as expected for backPain data", {
# Obtain number of parameters and log-likelihoods for equivalent
# "Six groups: one-dimensional" multinomial model presented in Table 5
# maximised log-likelihood
size <- tapply(backPainLong$count, backPainLong$id, sum)[backPainLong$id]
expect_equal(round(sum(stereotype$y * log(stereotype$fitted/size)), 2),
-151.55)
# number of parameters
expect_equal(stereotype$rank - nlevels(stereotype$eliminate), 12,
ignore_attr = TRUE)
})
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