context("apa.regression.glm")
library(apaformat)
x = testdata.apa.regression.glm
model = glm(Response ~ Attribute, data = x, family = binomial())
tab = apa.regression(model)
exp = matrix(byrow = T, nrow = 2,
c("0.45", "$z$ = -1.708", "(p > .05)",
"4.096", "$z$ = 2.976", "(p < .01)"))
rownames(exp) = c("(Intercept)", "Attribute")
colnames(exp) = c("Odds Ratio", "z score", "p-value")
expect_identical(tab, exp)
tab = apa.regression.glm(model)
exp = matrix(byrow = T, nrow = 2,
c("0.45", "$z$ = -1.708", "(p > .05)",
"4.096", "$z$ = 2.976", "(p < .01)"))
rownames(exp) = c("(Intercept)", "Attribute")
colnames(exp) = c("Odds Ratio", "z score", "p-value")
expect_identical(tab, exp)
ci = confint(model)
tab = apa.regression.glm(model, ci)
exp = matrix(byrow = T, nrow = 2,
c("0.45", "[0.16, 1.05]", "$z$ = -1.708", "(p > .05)",
"4.096", "[1.81, 12.14]", "$z$ = 2.976", "(p < .01)"))
rownames(exp) = c("(Intercept)", "Attribute")
colnames(exp) = c("Odds Ratio", "CI 95%", "z score", "p-value")
expect_identical(tab, exp)
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