melliotab: Create a formatted statistical table

In mellio: Polished, Editable Tables and Statistical Results

Create a formatted statistical table

Description

The main entry point for melliotab. Accepts data frames, model objects, or correlation matrices and formats them according to the specified citation style. Passing two or more model objects creates a side-by-side model comparison table.

Usage

## S3 method for class 'mediate'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'summary.mediate'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'medSummary'
melliotab(x, ..., section = NULL)

## S3 method for class 'medSummary2'
melliotab(x, ..., section = NULL)

## S3 method for class 'modmedSummary'
melliotab(x, ..., section = NULL)

## S3 method for class 'modmedSummary2'
melliotab(x, ..., section = NULL)

melliotab(x, ...)

## Default S3 method:
melliotab(x, ..., section = NULL)

## S3 method for class ''NULL''
melliotab(x, ...)

## S3 method for class 'character'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'summaryDefault'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'table'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'data.frame'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'lm'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  conf.int = TRUE,
  conf.level = 0.95,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'glm'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  conf.int = TRUE,
  exponentiate = FALSE,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'aov'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  effect_size = TRUE,
  ...
)

## S3 method for class 'htest'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'matrix'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  decimals = 2L,
  p_decimals = 3L,
  diagonal = "dash",
  triangle = "all",
  ...
)

## S3 method for class 'lavaan'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  what = NULL,
  section = NULL,
  standardized = TRUE,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'FitDiff'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  section = NULL,
  what = NULL,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

## S3 method for class 'fa'
melliotab(
  x,
  style = "apa7",
  title = NULL,
  number = NULL,
  note = NULL,
  source = NULL,
  section = NULL,
  what = NULL,
  cut = 0,
  sort = FALSE,
  decimals = 2L,
  p_decimals = 3L,
  ...
)

Arguments

x	A data.frame, model object (lm, glm, aov, htest), or correlation matrix
style	Citation style: "apa7" or "ieee"
title	Table title
number	Table number (integer or character)
note	Table note text
source	Table source text
decimals	Decimal places for estimates/statistics (1-4)
p_decimals	Decimal places for p-values (2-4)
...	Additional arguments passed to methods
section	Optional section selector for multi-section tables. Examples include "fit", "loadings", "paths", "covariances", "defined", "reliability", or "modification_indices" for structural model payloads; "loadings", "variance", or "fit" for EFA; and "comparison", "fit", or "diff" for FitDiff objects.
conf.int	Include confidence intervals (default TRUE)
conf.level	Confidence level (default 0.95)
exponentiate	Show exponentiated coefficients (odds ratios for logistic)
effect_size	Include effect size (eta-squared) for ANOVA
diagonal	Diagonal display: "dash" (em-dash), "one" (keep 1.00), "blank"
triangle	Which triangle to show: "all", "lower", "upper"
what	Backward-compatible alias for section in methods that previously used what. Prefer section.
standardized	Include standardized estimates (default TRUE)
cut	Minimum absolute loading to display (default 0, show all). Loadings below this threshold are shown as blank cells.
sort	Sort items by their primary loading (default FALSE)

Value

A melliotab object

Supported inputs

melliotab() is intended for table output inside R. It supports plain data frames, matrices, base table objects, correlation matrices, common model objects, hypothesis-test objects, and payloads created by mellio_payload(). For objects that can produce several tables, call melliotab(x) once to see the available section choices, then request one explicitly, for example melliotab(fit, section = "loadings").

Common modifiers

The ⁠mt_*()⁠ helpers are optional table modifiers. They follow the same pattern as many R table packages: create a table once, then add formatting only where needed. Common helpers include mt_title(), mt_note(), mt_decimals(), mt_format_ci(), mt_remove_leading_zeros(), mt_sig_stars(), mt_spanner(), mt_indent(), and mt_section_title().

Significance stars are never added by default. Use mt_sig_stars() only when that convention is appropriate for your manuscript, course, or journal.

Examples

# From a data frame
df <- data.frame(
  Variable = c("Age", "Gender"),
  B = c(0.45, -1.23),
  SE = c(0.12, 0.34),
  t = c(3.75, -3.62),
  p = c(0.0003, 0.0004)
)
melliotab(df, style = "apa7", title = "Regression Results")

# From a linear model
model <- lm(Ozone ~ Temp + Wind, data = airquality)
melliotab(model, style = "apa7", title = "Predictors of ozone concentration")

# Compare multiple models side by side
m1 <- lm(Ozone ~ Temp, data = airquality)
m2 <- lm(Ozone ~ Temp + Wind, data = airquality)
m3 <- lm(Ozone ~ Temp + Wind + Solar.R, data = airquality)
melliotab(
  m1, m2, m3,
  labels = c("Step 1", "Step 2", "Step 3"),
  dep.var.labels = "Ozone concentration"
)

mellio documentation built on Aug. 30, 2026, 1:06 a.m.