Nothing
mod <- list(
lm(mpg ~ hp, data = mtcars),
glm(vs ~ hp + cyl, data = mtcars, family = binomial)
)
# function inside glue string
st <- "{ifelse(p.value <0.001, 'Significant', 'Not significant')}"
tab <- modelsummary(mod, statistic = st, fmt = NULL, output = "dataframe")
expect_equivalent(tab[[4]][2], "Significant")
expect_equivalent(tab[[5]][2], "Not significant")
# glue + no statistic",{
tab <- modelsummary(
mod,
estimate = "**{estimate}** [{conf.low}, {conf.high}] ({p.value})",
statistic = NULL,
output = "data.frame",
gof_omit = ".*"
)
truth4 <- c(
"**30.099** [26.762, 33.436] (<0.001)",
"**-0.068** [-0.089, -0.048] (<0.001)",
""
)
truth5 <- c(
"**9.089** [4.102, 18.413] (0.006)",
"**-0.041** [-0.139, 0.013] (0.255)",
"**-0.690** [-2.499, 0.795] (0.382)"
)
expect_equivalent(tab[[4]], truth4)
expect_equivalent(tab[[5]], truth5)
# glue + multi statistics",{
tab <- modelsummary(
mod,
fmt = "%.3f",
estimate = "**{estimate}** [{conf.low}, {conf.high}]",
statistic = c(
"t={statistic}",
"p={p.value}"
),
output = "data.frame",
gof_omit = ".*"
)
truth4 <- c(
"**30.099** [26.762, 33.436]",
"t=18.421",
"p=0.000",
"**-0.068** [-0.089, -0.048]",
"t=-6.742",
"p=0.000",
"",
"",
""
)
truth5 <- c(
"**9.089** [4.102, 18.413]",
"t=2.759",
"p=0.006",
"**-0.041** [-0.139, 0.013]",
"t=-1.139",
"p=0.255",
"**-0.690** [-2.499, 0.795]",
"t=-0.873",
"p=0.382"
)
expect_equivalent(tab[[4]], truth4)
expect_equivalent(tab[[5]], truth5)
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