Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
library(huxtable)
is_latex <- guess_knitr_output_format() == "latex"
# knitr::knit_hooks$set(
# barrier = function(before, options, envir) {
# if (! before && is_latex) knitr::asis_output("\\FloatBarrier")
# }
# )
#
# if (is_latex) knitr::opts_chunk$set(barrier = TRUE)
options(huxtable.latex_siunitx_align = FALSE)
## -----------------------------------------------------------------------------
data(diamonds, package = "ggplot2")
diamonds <- diamonds[1:100,]
lm1 <- lm(price ~ carat + depth, diamonds)
lm2 <- lm(price ~ depth + factor(color, ordered = FALSE), diamonds)
lm3 <- lm(log(price) ~ carat + depth, diamonds)
## -----------------------------------------------------------------------------
huxreg(lm1, lm2, lm3)
## -----------------------------------------------------------------------------
color_names <- grep("factor", names(coef(lm2)), value = TRUE)
names(color_names) <- gsub(".*)(.)", "Color: \\1", color_names)
huxreg(lm1, lm2, lm3, coefs = c("Carat" = "carat", "Depth" = "depth", color_names))
## -----------------------------------------------------------------------------
diamond_regs <- huxreg(lm1, lm2, lm3)
diamond_regs[seq(8, 18, 2), 1] <- paste("Color:", LETTERS[5:10])
# prints the same as above
## -----------------------------------------------------------------------------
suppressPackageStartupMessages(library(dplyr))
diamond_regs %>%
map_background_color(-1, -1, by_regex(
"\\*" = "yellow"
)) %>%
set_italic(final(1), 1) %>%
set_caption("Linear regressions of diamond prices")
## -----------------------------------------------------------------------------
huxreg(lm1, lm3, error_pos = "right")
## -----------------------------------------------------------------------------
huxreg(lm1, lm3, error_pos = "same")
## -----------------------------------------------------------------------------
huxreg("Price" = lm1, "Log price" = lm3)
## -----------------------------------------------------------------------------
gl <- as_hux(broom::glance(lm1))
gl %>%
restack_down(cols = 3, on_remainder = "fill") %>%
set_bold(odds, everywhere)
## -----------------------------------------------------------------------------
huxreg(lm1, lm3, statistics = c("N. obs." = "nobs",
"R squared" = "r.squared", "F statistic" = "statistic",
"P value" = "p.value"))
## -----------------------------------------------------------------------------
huxreg(lm1, lm3, stars = c(`*` = 0.1, `**` = 0.05, `***` = 0.01)) # a little boastful?
## -----------------------------------------------------------------------------
# Another useful column: p.value
huxreg(
lm1, lm3,
error_format = "[{statistic}]",
note = "{stars}. T statistics in brackets."
)
## -----------------------------------------------------------------------------
huxreg(lm1, lm3, ci_level = .99, error_format = "({conf.low} -- {conf.high})")
## -----------------------------------------------------------------------------
huxreg(lm1, lm3, number_format = 2)
## -----------------------------------------------------------------------------
huxreg(lm1, lm3, bold_signif = 0.05)
## -----------------------------------------------------------------------------
library(lmtest)
library(sandwich)
lm_robust <- coeftest(lm1, vcov = vcovHC, save = TRUE)
huxreg("Normal SEs" = lm1, "Robust SEs" = lm_robust)
## -----------------------------------------------------------------------------
lm_fixed <- tidy_override(lm1, p.value = c(0.5, 0.2, 0.06))
huxreg("Normal p values" = lm1, "Supplied p values" = lm_fixed)
## -----------------------------------------------------------------------------
mnl <- nnet::multinom(gear ~ mpg, mtcars)
tidied <- broom::tidy(mnl)
models <- list()
models[["4 gears"]] <- tidy_replace(mnl, tidied[tidied$y.level == 4, ])
models[["5 gears"]] <- tidy_replace(mnl, tidied[tidied$y.level == 5, ])
huxreg(models, statistics = "AIC")
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