I'll use the example from the papaja
documentation as an example.
mod1 <- lm(Sepal.Length ~ Sepal.Width, data = iris)
mod2 <- update(mod1, formula = . ~ . + Petal.Length)
mod3 <- update(mod2, formula = . ~ . + Petal.Width)
moi <- list(Baseline = mod1, Length = mod2, Both = mod3)
h_reg <- apa_print(moi, boot_samples = 0)
h_reg_table <- h_reg$table
2) how do I remove rows like AIC
The table returned by apa_print()
is a data.frame
with some additional information. Hence, you can index and subset it as you would any other table. You can select rows by name (see below) or by row number.
# Remove rows
rows_to_remove <- c("$\\mathrm{AIC}$", "$\\mathrm{BIC}$")
h_reg_table <- h_reg_table[!rownames(h_reg_table) %in% rows_to_remove, ]
1) How do I add the asterisk to mark sig p values on the covariates
There is currently no way to highlight significant predictors (I'm not a fan of this practice). But here's some code that will let you add highlighting after the fact. The following function takes the formatted table, the list of the compared models and a character symbol to highlight significant predictors as input.
# Define custom function
highlight_sig_predictors <- function(x, models, symbol) {
n_coefs <- sapply(models, function(y) length(coef(y)))
for(i in seq_along(models)) {
sig_stars <- rep(FALSE, max(n_coefs))
sig_stars[1:n_coefs[i]] <- apply(confint(models[[i]]), 1, function(y) all(y > 0) || all(y < 0))
x[1:max(n_coefs), i] <- paste0(x[1:max(n_coefs), i], ifelse(sig_stars, symbol, paste0("\\phantom{", symbol, "}")))
}
x
}
Now this function can be used to customize the table returned by apa_print()
.
# Add significance symbols to predictors
h_reg_table <- highlight_sig_predictors(h_reg_table, moi, symbol = "*")
# Print table
apa_table(h_reg_table, escape = FALSE, align = c("lrrr"))