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Create publication-ready regression tables

Source: R/easytab.R
easytable.Rd

Takes model objects as arguments and creates formatted tables for Word or LaTeX/PDF output. Supports robust standard errors, marginal effects, and control variable grouping.

Usage

easytable(
  ...,
  model.names = NULL,
  output = "word",
  export.word = NULL,
  export.csv = NULL,
  robust.se = FALSE,
  control.var = NULL,
  margins = FALSE,
  highlight = FALSE,
  abbreviate = FALSE,
  table_size = "normalsize"
)

Arguments

...

Statistical model objects (lm or glm). Pass models directly like easytable(m1, m2, m3).

model.names

Character vector of custom names for model columns. If NULL (default), columns are named "Model 1", "Model 2", etc. Length must match number of models.

output

Character string specifying output format. One of:

  • "word" - Microsoft Word via flextable (default)

  • "latex" - LaTeX for PDF output

export.word

Character string ending in .docx for Word file export. Only supported when output = "word". If NULL (default), no file is written.

export.csv

Character string ending in .csv for CSV export. If NULL (default), no CSV file is written.

robust.se

Logical. Use robust standard errors (HC type)? Default FALSE. Requires packages: lmtest, sandwich

control.var

Character vector of variable names to group as "control variables". These will be collapsed into single rows showing "Y" for presence instead of individual coefficients. Default NULL.

margins

Logical. Compute average marginal effects (AME)? Default FALSE. Requires package: margins

highlight

Logical. Highlight significant coefficients (positive in green, negative in red)? Default FALSE. Works best with Word output.

abbreviate

Logical. Abbreviate variable names for readability? Default FALSE. When TRUE, long variable names are shortened using deterministic rules.

table_size

Character string specifying LaTeX table size. Only works with output = "latex". Options: "tiny", "small", "normalsize", "scriptsize". Default "normalsize". Error if used with Word output.

Value

Depends on output:

  • "word" - A flextable object

  • "latex" - Character string with LaTeX table code

Details

The function extracts coefficients, standard errors, and p-values from each model, adds significance stars (*** p<.01, ** p<.05, * p<.1), and includes model fit statistics (N, R-squared, Adjusted R-squared, AIC).

Control variables can be grouped to show presence/absence rather than individual coefficients for each factor level or transformation.

Term labels are automatically formatted for readability:

  • Factor levels separated with colon (e.g., advisor_confidence:low)

  • Interactions shown with asterisk (e.g., var1 * var2)

  • Polynomial contrasts as L indices (e.g., var:L1, var:L2)

  • Long variable names abbreviated for clarity

Dependencies

  • Always required: broom, dplyr

  • Word output: flextable

  • LaTeX output: knitr, optionally kableExtra for enhanced formatting

  • Robust SE: lmtest, sandwich

  • Marginal effects: margins

Examples

if (FALSE) {
# Load example data
library(palmerpenguins)
data(penguins)

# Fit models
m1 <- lm(body_mass_g ~ flipper_length_mm, data = penguins)
m2 <- lm(body_mass_g ~ flipper_length_mm + species, data = penguins)
m3 <- lm(body_mass_g ~ flipper_length_mm + species + island, data = penguins)

# Create table with default names (Model 1, Model 2, Model 3)
easytable(m1, m2, m3)

# Custom model names
easytable(m1, m2, m3, model.names = c("Baseline", "With Species", "Full"))

# LaTeX output
easytable(m1, m2, output = "latex")

# With robust standard errors
easytable(m1, m2, robust.se = TRUE)

# Group species and island as control variables
easytable(m1, m2, m3, control.var = c("species", "island"))

# Export to Word and CSV
easytable(m1, m2, export.word = "mytable.docx", export.csv = "mytable.csv")
}