Package 'apa7' reference manual

Title:	Writing Documents in American Psychological Association Style, Seventh Edition
Description:	Create American Psychological Association Style, Seventh Edition documents. Format numbers and text consistent with APA style. Create tables that comply with APA style by extending flextable functions.
Authors:	W. Joel Schneider [aut, cre, cph] (ORCID: <https://orcid.org/0000-0002-8393-5316>)
Maintainer:	W. Joel Schneider <[email protected]>
License:	CC0
Version:	0.1.3
Built:	2026-10-30 13:08:40 UTC
Source:	https://github.com/wjschne/apa7

Add break columns

Description

Add break columns

Usage

add_break_columns(
  d,
  ...,
  .before = FALSE,
  omit_first = FALSE,
  omit_last = FALSE
)
add_break_columns(
  d,
  ...,
  .before = FALSE,
  omit_first = FALSE,
  omit_last = FALSE
)

Arguments

d

data.frame or tibble

...

Column name or tidyselect function. Select columns

.before

insert break columns before selected columns (defaults to FALSE)

omit_first

omit the first break column

omit_last

omit the last break column

Value

data.frame or tibble

Examples

d <- data.frame(x_n = 3, x_mean = 4,
            y_n = 5, y_mean = 6,
            z_n = 4, z_mean = 4)
# Unquoted variable names
add_break_columns(d, x_mean)

# Character vector
add_break_columns(d, c("y_n", "z_n"),  .before = TRUE)

# Tidyselect function (contains, starts_with, ends_with,
# matches, num_range, all_of, any_of)
# Insert columns after all columns
# ending with "_mean" except the last instance
add_break_columns(d,
                  dplyr::ends_with("_mean"),
                  omit_last = TRUE)
d <- data.frame(x_n = 3, x_mean = 4,
            y_n = 5, y_mean = 6,
            z_n = 4, z_mean = 4)
# Unquoted variable names
add_break_columns(d, x_mean)

# Character vector
add_break_columns(d, c("y_n", "z_n"),  .before = TRUE)

# Tidyselect function (contains, starts_with, ends_with,
# matches, num_range, all_of, any_of)
# Insert columns after all columns
# ending with "_mean" except the last instance
add_break_columns(d,
                  dplyr::ends_with("_mean"),
                  omit_last = TRUE)

Make a column into a list column

Description

Make a column into a list column

Usage

add_list_column(
  data,
  ...,
  type = c("1", "a", "A", "I", "i"),
  sep = ". ",
  merge = FALSE
)
add_list_column(
  data,
  ...,
  type = c("1", "a", "A", "I", "i"),
  sep = ". ",
  merge = FALSE
)

Arguments

data

data.frame or tibble

...

Column name or tidyselect function. Select columns. Default is first column

type

list type. Can be "1" (numeric), "a" (lowercase alphabetical), or "ABC" (uppercase alphabetical), "i" (lowercase Roman numerals), "I" (uppercase Roman numerals)

sep

separator

merge

If TRUE, list columns will be united with their respective text columns.

Value

data.frame

Examples

d <- data.frame(x = letters[1:5], y = letters[2:6])
# default is first column
add_list_column(d) |>
  apa_flextable()
# select any column
add_list_column(d, y) |>
  apa_flextable()
add_list_column(d, type = "a", sep = ") ") |>
 apa_flextable()
add_list_column(d, merge = TRUE)
d <- data.frame(x = letters[1:5], y = letters[2:6])
# default is first column
add_list_column(d) |>
  apa_flextable()
# select any column
add_list_column(d, y) |>
  apa_flextable()
add_list_column(d, type = "a", sep = ") ") |>
 apa_flextable()
add_list_column(d, merge = TRUE)

Adds stars next to a column based on p-values

Description

Adds stars next to a column based on p-values

Usage

add_star_column(
  data,
  ...,
  p = "p",
  merge = FALSE,
  superscript = TRUE,
  star = "\\*",
  alpha = c(0.05, 0.01, 0.001),
  first_alpha_marginal = FALSE,
  add_trailing_space = FALSE,
  prefix = "\\"
)
add_star_column(
  data,
  ...,
  p = "p",
  merge = FALSE,
  superscript = TRUE,
  star = "\\*",
  alpha = c(0.05, 0.01, 0.001),
  first_alpha_marginal = FALSE,
  add_trailing_space = FALSE,
  prefix = "\\"
)

Arguments

data

data.frame or tibble

...

Column name or tidyselect function. Select columns

p

Column name or tidyselect function. Select p-value column name

merge

merge and balance columns (default: FALSE)

superscript

make as superscript

star

text for making stars

alpha

vector of thresholds

first_alpha_marginal

if TRUE, the first alpha value is treated as marginal and gets a dagger instead of a star

add_trailing_space

if TRUE, adds a trailing space after the stars (default: FALSE)

prefix

usually backslashes to prevent markdown from interpreting asterisks as bullets or italics

Value

data.frame

Examples

data.frame(b = c(1.4,2.2),
           p = c(.54, .02)) |>
 add_star_column(b, p)
data.frame(b = c(1.4,2.2),
           p = c(.54, .02)) |>
 add_star_column(b, p)

Align text on center text (default is decimal)

Description

Align text on center text (default is decimal)

Usage

align_chr(
  x,
  accuracy = NULL,
  trim_leading_zeros = FALSE,
  drop0trailing = FALSE,
  add_plusses = FALSE,
  padding_character = NULL,
  center = ".",
  format_integers = FALSE,
  side = c("both", "left", "right"),
  NA_value = "",
  format_numeric_character = FALSE,
  ...
)
align_chr(
  x,
  accuracy = NULL,
  trim_leading_zeros = FALSE,
  drop0trailing = FALSE,
  add_plusses = FALSE,
  padding_character = NULL,
  center = ".",
  format_integers = FALSE,
  side = c("both", "left", "right"),
  NA_value = "",
  format_numeric_character = FALSE,
  ...
)

Arguments

x

vector (numeric or character)

accuracy

number to round to. If NULL, the current default accuracy set with apa7_defaults() will be used.

trim_leading_zeros

if TRUE (default), trims leading zeros, otherwise keeps them

drop0trailing

Drop trailing zeros

add_plusses

if TRUE (default), adds a plus to positive numbers

padding_character

character to use for padding, default is ⁠&numsp;⁠ (figure space). With the default, text is padded to equal rendered width in the default font family (see num_pad() and the width_aware_padding argument of apa7_defaults()).

center

text on which to align text. Center on decimal by default, but can be any text.

format_integers

If TRUE, integers will be formatted with digits

side

side on which to make text of equal width

NA_value

value to replace NA

format_numeric_character

format character variables with numeric content

...

additional arguments passed to signs::signs()

Value

character vector

Examples

align_chr(c(1, 10, 100))
align_chr(c(1, 10, 100))

Make contingency table with chi-square test of independence

Description

Make contingency table with chi-square test of independence

Usage

apa_chisq(
  data,
  note = NULL,
  row_title_column = NULL,
  row_title_prefix = "",
  row_title_sep = " ",
  row_title_align = "center",
  row_title_border = list(color = "gray20", style = "solid", width = 1),
  left_column_padding = 20,
  cwidth = 0.75,
  cheight = 0.25,
  separate_headers = TRUE,
  apa_style = TRUE,
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  horizontal_padding = 3,
  table_align = "left",
  layout = "autofit",
  table_width = 1,
  markdown = TRUE,
  markdown_header = markdown,
  markdown_body = markdown,
  auto_format_columns = TRUE,
  column_formats = NULL,
  pretty_widths = TRUE,
  suppress_warnings = TRUE,
  ...
)
apa_chisq(
  data,
  note = NULL,
  row_title_column = NULL,
  row_title_prefix = "",
  row_title_sep = " ",
  row_title_align = "center",
  row_title_border = list(color = "gray20", style = "solid", width = 1),
  left_column_padding = 20,
  cwidth = 0.75,
  cheight = 0.25,
  separate_headers = TRUE,
  apa_style = TRUE,
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  horizontal_padding = 3,
  table_align = "left",
  layout = "autofit",
  table_width = 1,
  markdown = TRUE,
  markdown_header = markdown,
  markdown_body = markdown,
  auto_format_columns = TRUE,
  column_formats = NULL,
  pretty_widths = TRUE,
  suppress_warnings = TRUE,
  ...
)

Arguments

data

A two-column data.frame or tibble

note

Custom note (overrides automatic note.)

row_title_column

Column name or tidyselect function. column to group rows

row_title_prefix

text to be added to each title

row_title_sep

separator for prefix

row_title_align

alignment of row title ("left", "center", "right")

row_title_border

list of flextable styles

left_column_padding

Number of points the left column is padded (only relevant when there is a row_title_column and row_title_align = "left")

cwidth

initial cell width in inches

cheight

initial cell height in inches

separate_headers

separate header rows (default: TRUE)

apa_style

apply apa_style function (default: TRUE)

font_family

font family

font_size

font size

text_color

text color

border_color

border color

border_width

border width in pixels

line_spacing

spacing between lines

horizontal_padding

horizontal padding (in pixels)

table_align

table alignment ("left", "center", "right")

layout

table layout ("autofit", "fixed")

table_width

table width (in pixels, 0 for auto)

markdown

apply markdown formatting to header and body

markdown_header

apply markdown formatting to header

markdown_body

apply markdown formatting to body

auto_format_columns

if true, will attempt to format some columns automatically

column_formats

a column_formats object

pretty_widths

apply pretty_widths function

suppress_warnings

Suppress any warnings if true.

...

arguments passed to apa_style

Value

flextable::flextable

Examples

apa_chisq(mtcars[, c("am", "gear")])
apa_chisq(mtcars[, c("am", "gear")])

APA-formatted correlation table

Description

APA-formatted correlation table

Usage

apa_cor(
  data,
  note = NULL,
  p_value = c(0.05, 0.01, 0.001),
  digits = 2,
  bold_significant = FALSE,
  star_significant = TRUE,
  significance_note = TRUE,
  output = c("flextable", "tibble"),
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  table_width = 6.5,
  keep_empty_star_columns = TRUE,
  summary_functions = list(M = mean, SD = stats::sd),
  column_formats = NULL,
  ...
)
apa_cor(
  data,
  note = NULL,
  p_value = c(0.05, 0.01, 0.001),
  digits = 2,
  bold_significant = FALSE,
  star_significant = TRUE,
  significance_note = TRUE,
  output = c("flextable", "tibble"),
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  table_width = 6.5,
  keep_empty_star_columns = TRUE,
  summary_functions = list(M = mean, SD = stats::sd),
  column_formats = NULL,
  ...
)

Arguments

data

data.frame or tibble with variables to be

note

Custom note to appear below table. (Overrides automatic note.)

p_value

p-value needed to be flagged as significant

digits

Number of digits for rounding

bold_significant

bold significant correlations

star_significant

start significant correlations

significance_note

If TRUE, place note at bottom of table that significant correlations are bolded.

output

output type. Can be "flextable" or "tibble"

font_family

font family

font_size

font size

text_color

text color

border_color

border color

border_width

border width in pixels

line_spacing

spacing between lines

table_width

table width (in pixels, 0 for auto)

keep_empty_star_columns

Keep remove empty star columns (Default: TRUE)

summary_functions

Any named list of functions that summarize data columns (e.g., list(Mean = mean, SD = sd)). Can also be a character vector of function names (e.g., c("n", "M", "SD")). Functions available in a character vector: IQR, Interquartile Range, Kurtosis, MAD, Median Absolute Deviation, M, Mean, Med, Median, n, N, Quantile, Range, SD, Skewness, Var, Variance

column_formats

column_formats object

...

<data-masking> parameters passed to psych::corTest

Value

flextable::flextable

Examples

apa_cor(mtcars[, c("mpg", "am", "gear", "carb")])
apa_cor(mtcars[, c("mpg", "am", "gear", "carb")],
        output = "tibble",
        star_significant = FALSE)
apa_cor(mtcars[, c("mpg", "am", "gear", "carb")])
apa_cor(mtcars[, c("mpg", "am", "gear", "carb")],
        output = "tibble",
        star_significant = FALSE)

Convert data to flextable consistent with APA style

Description

The apa_flextable function performs a number of formatting operations on the data before and after the data are sent to flextable. See Details.

Usage

apa_flextable(
  data,
  row_title_column = NULL,
  row_title_align = "left",
  row_title_prefix = "",
  row_title_sep = " ",
  row_title_border = list(color = "gray20", style = "solid", width = 1),
  left_column_padding = 20,
  col_keys = colnames(data),
  cwidth = 0.75,
  cheight = 0.25,
  header_align_vertical = c("top", "middle", "bottom"),
  separate_headers = TRUE,
  apa_style = TRUE,
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  horizontal_padding = 3,
  table_align = "left",
  layout = "autofit",
  table_width = 1,
  markdown = TRUE,
  markdown_header = markdown,
  markdown_body = markdown,
  no_markdown_columns = NULL,
  no_markdown_columns_header = NULL,
  no_format_columns = NULL,
  auto_format_columns = TRUE,
  column_formats = NULL,
  pretty_widths = TRUE,
  add_breaks_between_spanners = TRUE,
  ...
)
apa_flextable(
  data,
  row_title_column = NULL,
  row_title_align = "left",
  row_title_prefix = "",
  row_title_sep = " ",
  row_title_border = list(color = "gray20", style = "solid", width = 1),
  left_column_padding = 20,
  col_keys = colnames(data),
  cwidth = 0.75,
  cheight = 0.25,
  header_align_vertical = c("top", "middle", "bottom"),
  separate_headers = TRUE,
  apa_style = TRUE,
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  horizontal_padding = 3,
  table_align = "left",
  layout = "autofit",
  table_width = 1,
  markdown = TRUE,
  markdown_header = markdown,
  markdown_body = markdown,
  no_markdown_columns = NULL,
  no_markdown_columns_header = NULL,
  no_format_columns = NULL,
  auto_format_columns = TRUE,
  column_formats = NULL,
  pretty_widths = TRUE,
  add_breaks_between_spanners = TRUE,
  ...
)

Arguments

data

data.frame or tibble

row_title_column

Column name or tidyselect function. column to group rows

row_title_align

alignment of row title ("left", "center", "right")

row_title_prefix

text to be added to each title

row_title_sep

separator for prefix

row_title_border

list of flextable styles

left_column_padding

Number of points the left column is padded (only relevant when there is a row_title_column and row_title_align = "left")

col_keys

column keys passed to flextable (defaults data column names)

cwidth

initial cell width in inches

cheight

initial cell height in inches

header_align_vertical

vertical alignment of headers. Can be "top", "middle", or "bottom"

separate_headers

separate header rows (default: TRUE)

apa_style

apply apa_style function (default: TRUE)

font_family

font family

font_size

font size

text_color

text color

border_color

border color

border_width

border width in pixels

line_spacing

spacing between lines

horizontal_padding

horizontal padding (in pixels)

table_align

table alignment ("left", "center", "right")

layout

table layout ("autofit", "fixed")

table_width

table width (in pixels, 0 for auto)

markdown

apply markdown formatting to header and body

markdown_header

apply markdown formatting to header

markdown_body

apply markdown formatting to body

no_markdown_columns

body columns that should not be treated as markdown

no_markdown_columns_header

column headers that should not be treated as markdown

no_format_columns

Column name or tidyselect function. selected columns are not formatted

auto_format_columns

if true, will attempt to format some columns automatically

column_formats

a column_formats object

pretty_widths

apply pretty_widths function

add_breaks_between_spanners

add breaks between spanners if TRUE

...

arguments passed to apa_style

Details

Roughly speaking, apa_flextable performs these operations by default:

Apply as_grouped_data and restructure row titles, if row_title is specified.
Format data with apa_format_columns if auto_format_columns = TRUE
Separate headers into multiple header rows if separate_headers = TRUE
Apply flextable::flextable
Apply flextable::surround to make borders to separate row groups, if any.
Apply the apa_style function (table formatting and markdown conversion) if apa_style = TRUE
Apply pretty_widths if pretty_widths = TRUE

Value

flextable::flextable

Examples

library(dplyr)
library(tidyr)
library(flextable)
mtcars %>%
  dplyr::select(vs, am, gear, carb) |>
  tidyr::pivot_longer(-vs,  names_to = "Variable") |>
  dplyr::summarise(Mean = round(mean(value), 2),
                   SD = round(sd(value), 2),
                   .by = c(Variable,vs)) |>
  dplyr::mutate(vs = factor(vs, levels = 0:1, labels = c("Automatic", "Manual"))) |>
  apa_flextable(row_title_column= vs,  row_title_align = "center") |>
  align(j = 2:3, align = "center")
library(dplyr)
library(tidyr)
library(flextable)
mtcars %>%
  dplyr::select(vs, am, gear, carb) |>
  tidyr::pivot_longer(-vs,  names_to = "Variable") |>
  dplyr::summarise(Mean = round(mean(value), 2),
                   SD = round(sd(value), 2),
                   .by = c(Variable,vs)) |>
  dplyr::mutate(vs = factor(vs, levels = 0:1, labels = c("Automatic", "Manual"))) |>
  apa_flextable(row_title_column= vs,  row_title_align = "center") |>
  align(j = 2:3, align = "center")

Format data columns

Description

Format data columns

Usage

apa_format_columns(
  data,
  column_formats = NULL,
  no_format_columns = NULL,
  rename_headers = TRUE,
  latex_headers = FALSE,
  format_separated_headers = TRUE,
  sep = "_",
  accuracy = NULL
)
apa_format_columns(
  data,
  column_formats = NULL,
  no_format_columns = NULL,
  rename_headers = TRUE,
  latex_headers = FALSE,
  format_separated_headers = TRUE,
  sep = "_",
  accuracy = NULL
)

Arguments

data

data set (data.frame or tibble)

column_formats

column_formats object. If NULL, the current default formatter set with apa7_defaults() will be used.

no_format_columns

Column name or tidyselect function. selected columns are not formatted

rename_headers

if TRUE, rename headers with markdown or latex

latex_headers

if TRUE, rename headers with latex instead of markdown

format_separated_headers

if TRUE, format headers with separated names. For example, if the formatter formats column R2 as ⁠*R*^2^⁠, then ⁠Model 1_R2⁠ becomes ⁠Model 1_*R*^2^⁠)

sep

separator for separated headers (default is "_")

accuracy

numeric (default: NULL, uses the current default accuracy set with apa7_defaults()). If not NULL, sets the accuracy for the formatter.

Value

tibble

Examples

lm(mpg ~ cyl + wt, data = mtcars) |>
  parameters::parameters() |>
  apa_format_columns() |>
  apa_flextable()
lm(mpg ~ cyl + wt, data = mtcars) |>
  parameters::parameters() |>
  apa_format_columns() |>
  apa_flextable()

print loadings

Description

print loadings

Usage

apa_loadings(
  fit,
  sort_loading = TRUE,
  min_loading = 0.2,
  column_formats = NULL,
  complexity = FALSE,
  uniqueness = FALSE
)
apa_loadings(
  fit,
  sort_loading = TRUE,
  min_loading = 0.2,
  column_formats = NULL,
  complexity = FALSE,
  uniqueness = FALSE
)

Arguments

fit

model fit object

sort_loading

sort table using psych::fa.sort

min_loading

minimum loading to display

column_formats

column_formats object to format columns. If NULL, the default column_formats is used.

complexity

print complexity column in factor analysis table

uniqueness

print uniqueness column in factor analysis table

Value

tibble

Examples

fit <- psych::fa(Harman74.cor$cov, 4, fm = "pa",rotate = "varimax")
apa_loadings(fit) |>
  `colnames<-`(c("Tests", "Verbal", "Spatial", "Quantitative", "Memory")) |>
  apa_flextable()
fit <- psych::fa(Harman74.cor$cov, 4, fm = "pa",rotate = "varimax")
apa_loadings(fit) |>
  `colnames<-`(c("Tests", "Verbal", "Spatial", "Quantitative", "Memory")) |>
  apa_flextable()

p-value in APA format

Description

p-value in APA format

Usage

apa_p(
  p,
  inline = FALSE,
  markdown = TRUE,
  min_digits = 2,
  max_digits = 3,
  align = FALSE
)
apa_p(
  p,
  inline = FALSE,
  markdown = TRUE,
  min_digits = 2,
  max_digits = 3,
  align = FALSE
)

Arguments

p

probability

inline

If TRUE (default), returns statistic (e.g., p = .04), otherwise just the number (e.g., .04)

markdown

By default, outputs text compatible with markdown if TRUE, otherwise prints plain text compatible with latex.

min_digits

minimum number of digits to round to. Default is 2.

max_digits

maximum number of digits to round to. Default is 3.

align

decimal alignment if TRUE

Value

character vector

Examples

# Values less than .001 are <.001
apa_p(.0002)
# Values between .001 and .01 are rounded to 3 digits
apa_p(.002)
# Values between .01 and .995 are rounded to 2 digits
apa_p(.02)#'
apa_p(.22)
apa_p(.994)
# Values above .995 are >.99
apa_p(.999)
# Rounding to 3 digits
apa_p(.2341, min_digits = 3)
apa_p(.0123, min_digits = 3)
apa_p(.00123, min_digits = 3)
apa_p(.000123, min_digits = 3)
apa_p(.991, min_digits = 3)
apa_p(.9991, min_digits = 3)
apa_p(.9995, min_digits = 3)
# Values less than .001 are <.001
apa_p(.0002)
# Values between .001 and .01 are rounded to 3 digits
apa_p(.002)
# Values between .01 and .995 are rounded to 2 digits
apa_p(.02)#'
apa_p(.22)
apa_p(.994)
# Values above .995 are >.99
apa_p(.999)
# Rounding to 3 digits
apa_p(.2341, min_digits = 3)
apa_p(.0123, min_digits = 3)
apa_p(.00123, min_digits = 3)
apa_p(.000123, min_digits = 3)
apa_p(.991, min_digits = 3)
apa_p(.9991, min_digits = 3)
apa_p(.9995, min_digits = 3)

Make star notes for p-values

Description

Make star notes for p-values

Usage

apa_p_star_note(x = c(0.05, 0.01, 0.001), first_alpha_marginal = FALSE)
apa_p_star_note(x = c(0.05, 0.01, 0.001), first_alpha_marginal = FALSE)

Arguments

x

vector of alpha values (p-value thresholds)

first_alpha_marginal

if TRUE, the first alpha value is treated as marginal and gets a dagger instead of a star

Value

character vector

Examples

apa_p_star_note()
apa_p_star_note(x = c(.10, .05, .01, .001), first_alpha_marginal = TRUE)
apa_p_star_note()
apa_p_star_note(x = c(.10, .05, .01, .001), first_alpha_marginal = TRUE)

format model parameters in APA style

Description

format model parameters in APA style

Usage

apa_parameters(
  fit,
  predictor_parameters = c("Coefficient", "SE", "Std_Coefficient", "t", "df_error", "p"),
  starred = NULL,
  bolded = NULL,
  column_formats = NULL,
  t_with_df = TRUE,
  ...
)

## S3 method for class 'lm'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Std_Coefficient", "t",
    "df_error", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  ...
)

## S3 method for class 'glm'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "t", "z",
    "df_error", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  ...
)

## S3 method for class 'polr'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "z", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  thresholds = TRUE,
  ...
)

## S3 method for class 'clm'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "z", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  thresholds = TRUE,
  ...
)

## S3 method for class 'merMod'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "t", "z",
    "df_error", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  random = TRUE,
  ...
)

## S3 method for class 'list'
apa_parameters(
  fit,
  predictor_parameters = NULL,
  starred = "deltaR2",
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  performance_parameters = c("R2", "deltaR2"),
  ...
)
apa_parameters(
  fit,
  predictor_parameters = c("Coefficient", "SE", "Std_Coefficient", "t", "df_error", "p"),
  starred = NULL,
  bolded = NULL,
  column_formats = NULL,
  t_with_df = TRUE,
  ...
)

## S3 method for class 'lm'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Std_Coefficient", "t",
    "df_error", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  ...
)

## S3 method for class 'glm'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "t", "z",
    "df_error", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  ...
)

## S3 method for class 'polr'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "z", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  thresholds = TRUE,
  ...
)

## S3 method for class 'clm'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "z", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  thresholds = TRUE,
  ...
)

## S3 method for class 'merMod'
apa_parameters(
  fit,
  predictor_parameters = c("Parameter", "Coefficient", "SE", "Exp_Coefficient", "t", "z",
    "df_error", "p"),
  starred = NA,
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  exponentiate = NULL,
  random = TRUE,
  ...
)

## S3 method for class 'list'
apa_parameters(
  fit,
  predictor_parameters = NULL,
  starred = "deltaR2",
  bolded = NA,
  column_formats = NULL,
  t_with_df = TRUE,
  performance_parameters = c("R2", "deltaR2"),
  ...
)

Arguments

fit

model fit object

predictor_parameters

predictor parameters to display. If named vector, column names will be vector names. Columns not present in the model output (e.g., t for a model tested with z) are silently dropped. For lists of models, NULL (default) uses the default for each model's class. Add "CI" to show confidence intervals as [LL, UL] (headed, e.g., "95% CI"), and, for glm, polr, and clm models, "Exp_CI" to show confidence intervals of exponentiated coefficients (headed, e.g., "95% CI for OR"). Confidence intervals are not shown by default.

starred

columns to star with significant p_values

bolded

columns to bold, if significant

column_formats

column_formats object to format columns. If NULL, the default column_formats is used.

t_with_df

if TRUE, the t column will be displayed with degrees of freedom in parentheses. If FALSE, only the t value is displayed.

...

arguments passed to methods. For lm, glm, polr, and clm models, further arguments are passed to parameters::model_parameters(). For example, vcov = "HC3" gives heteroskedasticity-consistent (robust) standard errors, and the test statistics, p-values, and confidence intervals are based on them. ci = .90 sets the confidence level.

exponentiate

if NULL (default), exponentiated coefficients are added when the model's link function is logit or log (i.e., odds ratios, risk ratios, or incidence rate ratios). If TRUE, exponentiated coefficients are always added. If FALSE, they are never added.

thresholds

for ordinal models, if TRUE (default), threshold (cutpoint) rows are displayed below the predictors.

random

for mixed models, if TRUE (default), random-effect standard deviations and correlations (and the residual standard deviation, for linear mixed models) are displayed below the fixed effects.

performance_parameters

for lists of models, model comparison metrics passed to apa_performance_comparison(). If NULL, no metrics are added. By default, R2 and deltaR2; for lists of mixed models (lme4), the default also includes the conditional R^2^ and its change (R2_conditional, deltaR2_conditional), and R2 is the marginal R^2^.

Details

For glm objects (including MASS::glm.nb), the test statistic is z for families with a fixed dispersion parameter (binomial, Poisson, negative binomial) and t for families with an estimated dispersion parameter (Gaussian, Gamma, inverse Gaussian, quasi families). Whichever statistic applies is displayed. The exponentiated coefficient column (Exp_Coefficient) is labeled OR for logit links, IRR for log links in count models (Poisson, quasi-Poisson, negative binomial), RR for log links in binomial models, and Exp(B) otherwise.

For ordinal regression models (MASS::polr and ordinal::clm), coefficients are tested with Wald z tests. (parameters reports t for polr, but the test is asymptotically normal, and clm reports z for the same model.) With a logit link, exponentiated coefficients are cumulative odds ratios, labeled OR. Threshold rows show only the estimate, its standard error, and its confidence interval, because their exponentiated values are not odds ratios, and testing whether a threshold equals 0 is not meaningful. Confidence intervals ("CI", "Exp_CI") are Wald z intervals, consistent with the z tests.

For mixed models fit with lme4 (lmer and glmer), fixed effects are displayed as for lm and glm models. For linear mixed models, t tests and confidence intervals use Kenward–Roger degrees of freedom by default (ci_method = "kenward", which requires the pbkrtest package); pass another ci_method (e.g., "satterthwaite", which requires lmerTest, or "wald") to change this. When the degrees of freedom differ across fixed effects, they are shown in a df column rather than in the t column header. Random-effect rows show only the estimated standard deviation (SD) or correlation (r), labeled by grouping factor.

Value

tibble

Examples

lm(mpg ~ cyl + wt, data = mtcars) |>
   apa_parameters() |>
   apa_flextable()

# Confidence intervals with robust (HC3) standard errors
lm(mpg ~ cyl + wt, data = mtcars) |>
   apa_parameters(
     predictor_parameters = c("Parameter", "Coefficient", "SE", "CI", "t", "df_error", "p"),
     vcov = "HC3"
   ) |>
   apa_flextable()
glm(am ~ wt + hp, data = mtcars, family = binomial) |>
   apa_parameters() |>
   apa_flextable()
MASS::polr(poverty ~ gender + age, data = carData::WVS, Hess = TRUE) |>
   apa_parameters()
if (requireNamespace("lme4", quietly = TRUE) &&
    requireNamespace("pbkrtest", quietly = TRUE)) {
  lme4::lmer(Reaction ~ Days + (Days | Subject), data = lme4::sleepstudy) |>
    apa_parameters()
}
lm(mpg ~ cyl + wt, data = mtcars) |>
   apa_parameters() |>
   apa_flextable()

# Confidence intervals with robust (HC3) standard errors
lm(mpg ~ cyl + wt, data = mtcars) |>
   apa_parameters(
     predictor_parameters = c("Parameter", "Coefficient", "SE", "CI", "t", "df_error", "p"),
     vcov = "HC3"
   ) |>
   apa_flextable()
glm(am ~ wt + hp, data = mtcars, family = binomial) |>
   apa_parameters() |>
   apa_flextable()
MASS::polr(poverty ~ gender + age, data = carData::WVS, Hess = TRUE) |>
   apa_parameters()
if (requireNamespace("lme4", quietly = TRUE) &&
    requireNamespace("pbkrtest", quietly = TRUE)) {
  lme4::lmer(Reaction ~ Days + (Days | Subject), data = lme4::sleepstudy) |>
    apa_parameters()
}

format model performance metrics in APA style

Description

format model performance metrics in APA style

Usage

apa_performance(fit, metrics = c("R2", "Sigma"), column_formats = NULL)

## S3 method for class 'lm'
apa_performance(fit, metrics = c("R2", "Sigma"), column_formats = NULL)

## S3 method for class 'glm'
apa_performance(fit, metrics = c("R2", "AIC"), column_formats = NULL)

## S3 method for class 'polr'
apa_performance(fit, metrics = c("R2", "AIC"), column_formats = NULL)

## S3 method for class 'clm'
apa_performance(fit, metrics = c("R2", "AIC"), column_formats = NULL)

## S3 method for class 'merMod'
apa_performance(
  fit,
  metrics = c("R2_marginal", "R2_conditional", "ICC"),
  column_formats = NULL
)

## S3 method for class 'list'
apa_performance(fit, metrics = NULL, column_formats = NULL)
apa_performance(fit, metrics = c("R2", "Sigma"), column_formats = NULL)

## S3 method for class 'lm'
apa_performance(fit, metrics = c("R2", "Sigma"), column_formats = NULL)

## S3 method for class 'glm'
apa_performance(fit, metrics = c("R2", "AIC"), column_formats = NULL)

## S3 method for class 'polr'
apa_performance(fit, metrics = c("R2", "AIC"), column_formats = NULL)

## S3 method for class 'clm'
apa_performance(fit, metrics = c("R2", "AIC"), column_formats = NULL)

## S3 method for class 'merMod'
apa_performance(
  fit,
  metrics = c("R2_marginal", "R2_conditional", "ICC"),
  column_formats = NULL
)

## S3 method for class 'list'
apa_performance(fit, metrics = NULL, column_formats = NULL)

Arguments

fit

model fit object

metrics

performance metrics. Default is R2 and Sigma

column_formats

column_formats object to format columns. If NULL, the default column_formats is used.

Details

For glm objects, R2 is the pseudo-R^2^ that performance::r2() selects for the model family (e.g., Tjur's R^2^ for logistic regression and Nagelkerke's R^2^ for count models). The header names the pseudo-R^2^ that was used. Because the residual standard deviation is not meaningful for most GLMs, the default metrics are R2 and AIC.

For mixed models (lme4::lmer and lme4::glmer), the default metrics are the marginal R^2^ (variance explained by the fixed effects), the conditional R^2^ (fixed and random effects), and the intraclass correlation (ICC), as computed by performance::model_performance().

For a list of models, each model's metrics are displayed in a row, labeled in a Model column by the list's names (or "Model 1", "Model 2", ... for unnamed elements). If metrics is NULL (default), each model's default metrics are used.

Value

tibble

Examples

lm(mpg ~ cyl + wt, data = mtcars) |>
   apa_performance() |>
   apa_flextable()
list(
  `Cylinders` = lm(mpg ~ cyl, data = mtcars),
  `Cylinders and weight` = lm(mpg ~ cyl + wt, data = mtcars)
) |>
  apa_performance()
lm(mpg ~ cyl + wt, data = mtcars) |>
   apa_performance() |>
   apa_flextable()
list(
  `Cylinders` = lm(mpg ~ cyl, data = mtcars),
  `Cylinders and weight` = lm(mpg ~ cyl + wt, data = mtcars)
) |>
  apa_performance()

format model comparison metrics in APA style

Description

format model comparison metrics in APA style

Usage

apa_performance_comparison(
  ...,
  metrics = NULL,
  starred = NA,
  column_formats = NULL
)
apa_performance_comparison(
  ...,
  metrics = NULL,
  starred = NA,
  column_formats = NULL
)

Arguments

...

model fit objects, or a list of them. Models are labeled by the list's names (or the argument names), and "Model 1", "Model 2", ... for unnamed models.

metrics

performance metrics. If NULL (default), R2, deltaR2, F, and p for models with an estimated dispersion parameter (e.g., lm, Gaussian or quasi-family glm), and R2, deltaR2, Chi2, df, and p for GLMs with a fixed dispersion parameter (binomial, Poisson, negative binomial). Use "all" for all available metrics.

starred

columns to star with significant p_values

column_formats

column_formats object to format columns. If NULL, the default column_formats is used.

Details

Nested models are compared with F tests (performance::test_wald()) unless every model is a GLM with a fixed dispersion parameter, in which case likelihood ratio tests (performance::test_likelihoodratio()) are used. For GLMs, R2 is the pseudo-R^2^ that performance::r2() selects for the model family, and the header names it (e.g., R^2^~Tjur~).

Mixed models (lme4::lmer and lme4::glmer) are compared with likelihood ratio tests. R2 is the marginal R^2^ (variance explained by the fixed effects), and by default the conditional R^2^ (fixed and random effects) and its change (R2_conditional, deltaR2_conditional) are shown too, because adding random effects changes the conditional but not the marginal R^2^.

Value

tibble

Examples

m1 <- lm(mpg ~ cyl, data = mtcars)
m2 <- lm(mpg ~ cyl + wt, data = mtcars)
apa_performance_comparison(list(`Model 1` =m1, `Model 3` =m2)) |>
   apa_flextable()
m1 <- lm(mpg ~ cyl, data = mtcars)
m2 <- lm(mpg ~ cyl + wt, data = mtcars)
apa_performance_comparison(list(`Model 1` =m1, `Model 3` =m2)) |>
   apa_flextable()

Style `flextable::flextable` object according to APA style

Description

Style flextable::flextable object according to APA style

Usage

apa_style(
  x,
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  horizontal_padding = 3,
  table_align = "left",
  header_align_vertical = c("top", "middle", "bottom"),
  layout = "autofit",
  table_width = 0,
  markdown = TRUE,
  markdown_header = markdown,
  markdown_body = markdown,
  no_markdown_columns = NULL,
  no_markdown_columns_header = no_markdown_columns,
  separate_headers = TRUE
)
apa_style(
  x,
  font_family = NULL,
  font_size = 12,
  text_color = "black",
  border_color = "black",
  border_width = 0.5,
  line_spacing = 2,
  horizontal_padding = 3,
  table_align = "left",
  header_align_vertical = c("top", "middle", "bottom"),
  layout = "autofit",
  table_width = 0,
  markdown = TRUE,
  markdown_header = markdown,
  markdown_body = markdown,
  no_markdown_columns = NULL,
  no_markdown_columns_header = no_markdown_columns,
  separate_headers = TRUE
)

Arguments

x

object

font_family

font family

font_size

font size

text_color

text color

border_color

border color

border_width

border width in pixels

line_spacing

spacing between lines

horizontal_padding

horizontal padding (in pixels)

table_align

table alignment ("left", "center", "right")

header_align_vertical

vertical alignment of headers. Can be "top", "middle", or "bottom"

layout

table layout ("autofit", "fixed")

table_width

table width (in pixels, 0 for auto)

markdown

apply markdown formatting to header and body

markdown_header

apply markdown formatting to header

markdown_body

apply markdown formatting to body

no_markdown_columns

body columns that should not be treated as markdown

no_markdown_columns_header

column headers that should not be treated as markdown

separate_headers

separate headers into column spanner labels

Value

object

Examples

d <- data.frame(x = 1:3, y = 4:6)
flextable::flextable(d) |>
  apa_style()
d <- data.frame(x = 1:3, y = 4:6)
flextable::flextable(d) |>
  apa_style()

Set defaults for apa7 package

Description

Set defaults for apa7 package

Usage

apa7_defaults(
  accuracy = NULL,
  font_family = NULL,
  intercept_text = NULL,
  column_formats = NULL,
  number_formatter = NULL,
  trim_leading_zero = NULL,
  width_aware_padding = NULL,
  reset = FALSE
)
apa7_defaults(
  accuracy = NULL,
  font_family = NULL,
  intercept_text = NULL,
  column_formats = NULL,
  number_formatter = NULL,
  trim_leading_zero = NULL,
  width_aware_padding = NULL,
  reset = FALSE
)

Arguments

accuracy

numeric (default: .01)

font_family

font family

intercept_text

what to call the intercept

column_formats

column formatting functions

number_formatter

default function to format numbers

trim_leading_zero

default function to trim leading zeros from numbers

width_aware_padding

if TRUE (default), align_chr() pads text to equal rendered width in font_family (when the font is installed). If FALSE, text is padded with one figure space per missing character.

reset

if TRUE, reset all defaults (except as specified)

Value

previous defaults

Examples

apa7_defaults(accuracy = .001)
# Reset to package defaults
apa7_defaults(reset = TRUE)
apa7_defaults(accuracy = .001)
# Reset to package defaults
apa7_defaults(reset = TRUE)

Tables ready for `apa_flextable`

Description

The tibbles returned by apa_parameters(), apa_performance(), and apa_performance_comparison() have class apa7_tbl. They are ordinary tibbles for post-processing with dplyr, but in knitr and Quarto documents they are rendered as an apa_flextable() automatically. In the console they print as tibbles.

Usage

## S3 method for class 'apa7_tbl'
print(x, ...)

## S3 method for class 'apa7_tbl'
knit_print(x, ...)
## S3 method for class 'apa7_tbl'
print(x, ...)

## S3 method for class 'apa7_tbl'
knit_print(x, ...)

Arguments

x

an apa7_tbl

...

arguments passed to the next method

Details

The apa7.print option controls this behavior:

"auto" (default): flextable in knitr/Quarto, tibble in the console.
"flextable": flextable everywhere.
"tibble": tibble everywhere.

To render with non-default settings, pass the table to apa_flextable() explicitly, which always returns a flextable.

Value

x, invisibly, for print. A knit_asis or flextable output for knit_print.

Examples

fit <- lm(mpg ~ cyl + wt, data = mtcars)
# Prints as a tibble in the console
apa_parameters(fit)

# It is still a tibble, so it can be post-processed
apa_parameters(fit) |>
  dplyr::filter(Variable != "Constant") |>
  apa_flextable()
fit <- lm(mpg ~ cyl + wt, data = mtcars)
# Prints as a tibble in the console
apa_parameters(fit)

# It is still a tibble, so it can be post-processed
apa_parameters(fit) |>
  dplyr::filter(Variable != "Constant") |>
  apa_flextable()

Column format class

Description

This class is used to define the format of columns in tables, including the name, header, latex representation, and a formatter function.

Usage

column_format(
  name = character(0),
  header = character(0),
  latex = character(0),
  formatter = function() NULL
)
column_format(
  name = character(0),
  header = character(0),
  latex = character(0),
  formatter = function() NULL
)

Arguments

name

name of column

markdown representation of header name

latex

latex representation of header name

formatter

function that formats the column values. It should take a vector of values and return a character vector of formatted values.

Value

column_format object

Examples

R2 <- column_format(
         "R2",
         header = "*R*^2^",
         latex = "$R^2$",
         formatter = \(x, accuracy = the$accuracy, ...) {
                       align_chr(x,
                                 accuracy = accuracy,
                                 trim_leading_zeros = TRUE,
                                 ...)
                       })
R2
R2@header
R2@formatter
R2 <- column_format(
         "R2",
         header = "*R*^2^",
         latex = "$R^2$",
         formatter = \(x, accuracy = the$accuracy, ...) {
                       align_chr(x,
                                 accuracy = accuracy,
                                 trim_leading_zeros = TRUE,
                                 ...)
                       })
R2
R2@header
R2@formatter

Create a set of column formats

Description

Returns an S7 object that contains a list of column_format objects that can be used to format parameters in APA style.

Usage

column_formats(
  .data = NULL,
  accuracy = NULL,
  intercept_text = NULL,
  starred_columns = character(0),
  variable_labels = character(0),
  custom_columns = NULL
)
column_formats(
  .data = NULL,
  accuracy = NULL,
  intercept_text = NULL,
  starred_columns = character(0),
  variable_labels = character(0),
  custom_columns = NULL
)

Arguments

.data

list of column_format objects

accuracy

numeric (passed to scales::number)

intercept_text

describe intercept

starred_columns

which columns get p-value stars

variable_labels

named vector of variable names (with vector names as labels). For example, c(⁠Parental Income⁠ = "parental_income", ⁠Number of Siblings⁠ = "n_siblings")

custom_columns

named list of column_formats to add or replace existing columns

Value

column_formats

Slots

get_column_names: getter for column names
get_headers: getter for column headers
get_latex: getter for column latex headers
get_formatters: getter for column formatters
get_header_rename: getter for column names with headers as names
get_header_rename_latex: getter for column names with latex headers as names
get_tibble: getter for tibble with column names, headers, latex headers, and formatters

Examples

my_formatter <- column_formats()
my_formatter$Coefficient@formatter <- \(x) round(x, 2)
my_formatter$Coefficient@formatter(2.214)
my_formatter <- column_formats()
my_formatter$Coefficient@formatter <- \(x) round(x, 2)
my_formatter$Coefficient@formatter(2.214)

Prepend column spanner labels to data column labels

Description

Prepend column spanner labels to data column labels

Usage

column_spanner_label(data, label, ..., relocate = TRUE)
column_spanner_label(data, label, ..., relocate = TRUE)

Arguments

data

data.frame or tibble

label

character of column spanner

...

columns (i.e., one or more tidyselect functions and/or a vector of quoted or unquoted variable names)

relocate

relocate columns with same spanner label to be adjacent

Value

data.frame or tibble

Examples

d <- data.frame(y = 1:3, x1 = 2:4, x2 = 3:5)

# Unquoted variable names
column_spanner_label(d, "Label", c(x1, x2))
# Character values (quoted variable names)
column_spanner_label(d, "Label", c("x1", "x2"))
# Tidyselect function (e.g., starts_with, ends_with, contains)
column_spanner_label(d, "Label", dplyr::starts_with("x"))
# Tidyselect range
column_spanner_label(d, "Label", x1:x2)
# Selected variables are relocated after the first selected variable
column_spanner_label(d, "Label", c(x2, y))
d <- data.frame(y = 1:3, x1 = 2:4, x2 = 3:5)

# Unquoted variable names
column_spanner_label(d, "Label", c(x1, x2))
# Character values (quoted variable names)
column_spanner_label(d, "Label", c("x1", "x2"))
# Tidyselect function (e.g., starts_with, ends_with, contains)
column_spanner_label(d, "Label", dplyr::starts_with("x"))
# Tidyselect range
column_spanner_label(d, "Label", x1:x2)
# Selected variables are relocated after the first selected variable
column_spanner_label(d, "Label", c(x2, y))

Return markdown text with hanging indent

Description

Return markdown text with hanging indent

Usage

hanging_indent(
  x,
  indent = 4,
  width = 30,
  space = NULL,
  newline = "\\\\\n",
  whitespace_only = FALSE,
  wrap_equal_width = FALSE
)
hanging_indent(
  x,
  indent = 4,
  width = 30,
  space = NULL,
  newline = "\\\\\n",
  whitespace_only = FALSE,
  wrap_equal_width = FALSE
)

Arguments

x

text

indent

number of spaces to indent

width

number of characters to break lines

space

indenting space character (defaults to non-breaking space)

newline

text for creating new line

whitespace_only

wrapping spaces only

wrap_equal_width

Attempts to split lines to make them of approximately equal width

Value

character vector

Examples

hanging_indent("Hello Darkness, my old friend. I've come to talk with you again.")
hanging_indent("Hello Darkness, my old friend. I've come to talk with you again.")

Installs the apaquarto extension.

Description

A wrapper for quarto::quarto_add_extension

Usage

install_apaquarto(
  no_prompt = FALSE,
  quiet = FALSE,
  quarto_args = NULL,
  ask = TRUE
)
install_apaquarto(
  no_prompt = FALSE,
  quiet = FALSE,
  quarto_args = NULL,
  ask = TRUE
)

Arguments

no_prompt

Do not prompt to confirm approval to download external extension.

quiet

Suppress warning and other messages

quarto_args

Character vector of other quarto CLI arguments to append to the Quarto command executed by this function.

ask

if TRUE (default), ask before installing missing packages. If FALSE, install missing packages without asking.

Value

installs the apaquarto Quarto extension

Examples

## Not run: 
install_apaquarto()

## End(Not run)
## Not run: 
install_apaquarto()

## End(Not run)

Tests if a character vector contains numeric-like values

Description

Tests if a character vector contains numeric-like values

Usage

is_numeric_like(x, elementwise = FALSE)
is_numeric_like(x, elementwise = FALSE)

Arguments

x

character vector

elementwise

if TRUE, returns a logical vector for each element, otherwise returns a single logical value indicating if all elements are numeric-like (default: FALSE)

Value

logical vector

Examples

is_numeric_like(c("-9", " 2.0", "-1.0 "))
is_numeric_like(c("9-", -1, "10"))
is_numeric_like(c("9", -1.2, "10"))
is_numeric_like(c("-9", " 2.0", "-1.0 "))
is_numeric_like(c("9-", -1, "10"))
is_numeric_like(c("9", -1.2, "10"))

Run shiny app to make a document in APA style via Quarto

Description

A wrapper for shiny::runGitHub Note that running this function will install any missing packages needed to run the app: bsicons, bslib, conflicted, dplyr, fresh, purrr, ragg, rclipboard, readr, shiny, shinyWidgets, snakecase, svglite, tibble, tidyr, tippy, toastui, yaml

Usage

make_apaquarto(launch.browser = TRUE, ask = TRUE)
make_apaquarto(launch.browser = TRUE, ask = TRUE)

Arguments

launch.browser

run shiny app in default browser

ask

if TRUE (default), ask before installing missing packages. If FALSE, install missing packages without asking.

Value

Runs a shiny app that creates apaquarto documents

Examples

## Not run: 
make_apaquarto()

## End(Not run)
## Not run: 
make_apaquarto()

## End(Not run)

Display latex matrices

Description

Display latex matrices

Usage

matrix_display(x, bracket = c("[", "(", "|", ""), include_names = TRUE)
matrix_display(x, bracket = c("[", "(", "|", ""), include_names = TRUE)

Arguments

x

a matrix

bracket

type of bracket: bmatrix, Bmatrix, pmatrix, vmatrix, Vmatrix, , matrix

Value

character

Examples

matrix_display(diag(2))
matrix_display(diag(2))

Pads text on the left or right so that the width is the same for each element of the vector

Description

By default, text is padded with one padding_character per missing visible character. Markdown markup (e.g., ⁠**⁠, *, ^, ~, and backslash escapes) is not counted. If font_family names an installed font, text is instead padded to equal rendered width in that font, using a combination of figure, punctuation, thin, and hair spaces (padding_character is then ignored). Superscripts and subscripts are measured at 2/3 of the font size.

Usage

num_pad(
  x,
  pad_left = TRUE,
  padding_character = "&numsp;",
  NA_value = "",
  font_family = NULL
)
num_pad(
  x,
  pad_left = TRUE,
  padding_character = "&numsp;",
  NA_value = "",
  font_family = NULL
)

Arguments

x

vector of text

pad_left

if TRUE (default), pads on the left, otherwise pads on the right

padding_character

character to use for padding, default is ⁠&numsp;⁠ (figure space)

NA_value

value to replace NA

font_family

font in which to measure text widths. If NULL (default) or NA, or if the font is not installed, widths are counted in characters.

Value

character vector

Examples

num_pad(c("a", "bb"))
num_pad(c("−1", "1"), font_family = "Times New Roman")
num_pad(c("a", "bb"))
num_pad(c("−1", "1"), font_family = "Times New Roman")

Convert p-values to stars

Description

Convert p-values to stars

Usage

p2stars(
  p,
  alpha = c(0.05, 0.01, 0.001),
  first_alpha_marginal = FALSE,
  superscript = FALSE,
  add_trailing_space = FALSE,
  prefix = "\\"
)
p2stars(
  p,
  alpha = c(0.05, 0.01, 0.001),
  first_alpha_marginal = FALSE,
  superscript = FALSE,
  add_trailing_space = FALSE,
  prefix = "\\"
)

Arguments

p

vector of numbers

alpha

vector of thresholds

first_alpha_marginal

if TRUE, the first alpha value is treated as marginal and gets a dagger instead of a star

superscript

make as superscript

add_trailing_space

if TRUE, adds a trailing space after the stars (default: FALSE)

prefix

usually backslashes to prevent markdown from interpreting asterisks as bullets or italics

Value

character vector

Examples

p2stars(c(.32, .02, .005),
        alpha = c(.05, .01))
p2stars(c(.32, .02, .005),
        alpha = c(.05, .01))

A wrapper for tidyr::pivot_wider that creates columns names as `name_variable` instead of `variable_name`

Description

The default for names_vary is "slowest" instead of the usual "fastest".

Usage

pivot_wider_name_first(
  data,
  ...,
  id_cols = NULL,
  id_expand = FALSE,
  names_from = name,
  names_prefix = "",
  names_sep = "_",
  names_sort = FALSE,
  names_vary = "slowest",
  names_expand = FALSE,
  names_repair = "check_unique",
  values_from = value,
  values_fill = NULL,
  values_fn = NULL,
  unused_fn = NULL
)
pivot_wider_name_first(
  data,
  ...,
  id_cols = NULL,
  id_expand = FALSE,
  names_from = name,
  names_prefix = "",
  names_sep = "_",
  names_sort = FALSE,
  names_vary = "slowest",
  names_expand = FALSE,
  names_repair = "check_unique",
  values_from = value,
  values_fill = NULL,
  values_fn = NULL,
  unused_fn = NULL
)

Arguments

data

A data frame to pivot.

...

Additional arguments passed on to methods.

id_cols

<tidy-select> A set of columns that uniquely identify each observation. Typically used when you have redundant variables, i.e. variables whose values are perfectly correlated with existing variables.

Defaults to all columns in data except for the columns specified through names_from and values_from. If a tidyselect expression is supplied, it will be evaluated on data after removing the columns specified through names_from and values_from.

id_expand

Should the values in the id_cols columns be expanded by expand() before pivoting? This results in more rows, the output will contain a complete expansion of all possible values in id_cols. Implicit factor levels that aren't represented in the data will become explicit. Additionally, the row values corresponding to the expanded id_cols will be sorted.

names_from, values_from

<tidy-select> A pair of arguments describing which column (or columns) to get the name of the output column (names_from), and which column (or columns) to get the cell values from (values_from).

If values_from contains multiple values, the value will be added to the front of the output column.

names_prefix

String added to the start of every variable name. This is particularly useful if names_from is a numeric vector and you want to create syntactic variable names.

names_sep

If names_from or values_from contains multiple variables, this will be used to join their values together into a single string to use as a column name.

names_sort

Should the column names be sorted? If FALSE, the default, column names are ordered by first appearance.

names_vary

When names_from identifies a column (or columns) with multiple unique values, and multiple values_from columns are provided, in what order should the resulting column names be combined?

"fastest" varies names_from values fastest, resulting in a column naming scheme of the form: ⁠value1_name1, value1_name2, value2_name1, value2_name2⁠. This is the default.
"slowest" varies names_from values slowest, resulting in a column naming scheme of the form: ⁠value1_name1, value2_name1, value1_name2, value2_name2⁠.

names_expand

Should the values in the names_from columns be expanded by expand() before pivoting? This results in more columns, the output will contain column names corresponding to a complete expansion of all possible values in names_from. Implicit factor levels that aren't represented in the data will become explicit. Additionally, the column names will be sorted, identical to what names_sort would produce.

names_repair

What happens if the output has invalid column names? The default, "check_unique" is to error if the columns are duplicated. Use "minimal" to allow duplicates in the output, or "unique" to de-duplicated by adding numeric suffixes. See vctrs::vec_as_names() for more options.

values_fill

Optionally, a (scalar) value that specifies what each value should be filled in with when missing.

This can be a named list if you want to apply different fill values to different value columns.

values_fn

Optionally, a function applied to the value in each cell in the output. You will typically use this when the combination of id_cols and names_from columns does not uniquely identify an observation.

This can be a named list if you want to apply different aggregations to different values_from columns.

unused_fn

Optionally, a function applied to summarize the values from the unused columns (i.e. columns not identified by id_cols, names_from, or values_from).

The default drops all unused columns from the result.

This can be a named list if you want to apply different aggregations to different unused columns.

id_cols must be supplied for unused_fn to be useful, since otherwise all unspecified columns will be considered id_cols.

This is similar to grouping by the id_cols then summarizing the unused columns using unused_fn.

Value

data.frame

Examples

d <- data.frame(Model = paste0("Model","_", 1:2), t = 1:2, p = c(.05, .45))
pivot_wider_name_first(d, names_from = Model, values_from = c(t, p))
# For comparison:
tidyr::pivot_wider(d, names_from = Model, values_from = c(t, p))
d <- data.frame(Model = paste0("Model","_", 1:2), t = 1:2, p = c(.05, .45))
pivot_wider_name_first(d, names_from = Model, values_from = c(t, p))
# For comparison:
tidyr::pivot_wider(d, names_from = Model, values_from = c(t, p))

Use flextable::dim_pretty to fit column widths

Description

Use flextable::dim_pretty to fit column widths

Usage

pretty_widths(
  x,
  min_width = 0.05,
  unit = c("in", "cm", "mm"),
  table_width = 6.5
)
pretty_widths(
  x,
  min_width = 0.05,
  unit = c("in", "cm", "mm"),
  table_width = 6.5
)

Arguments

x

flextable

min_width

minimum width of columns

unit

Can be ⁠in⁠, cm, or mm

table_width

width of table

Value

flextable::flextable

Scientific notation for markdown

Description

Scientific notation for markdown

Usage

sci_md(x, digits = 2, lb = 0.0095, ub = 99.5, align = FALSE)
sci_md(x, digits = 2, lb = 0.0095, ub = 99.5, align = FALSE)

Arguments

x

Numeric vector

digits

number of digits of precision

lb

lower bound where scientific notation is turned on

ub

upper bound where scientific notation is turned on

align

decimal align

Value

A character vector

Examples

sci_md(c(.0045,1.44, 24567857.45))
sci_md(c(.0045,1.44, 24567857.45))

Add columns that separate significance stars from numbers

Description

Add columns that separate significance stars from numbers

Usage

separate_star_column(
  data,
  ...,
  superscript = TRUE,
  star = "\\*",
  star_replace = "\\\\*"
)
separate_star_column(
  data,
  ...,
  superscript = TRUE,
  star = "\\*",
  star_replace = "\\\\*"
)

Arguments

data

data.frame or tibble

...

Column name or tidyselect function. Select columns

superscript

make stars superscript

star

character to use for stars (default: "\*")

star_replace

character to replace stars with (default: "\\*")

Value

data.frame or tibble

Examples

tibble::tibble(x = c(".45", ".58*", ".68**"),
               y = c(1,2,3),
               z = 4:6) |>
               separate_star_column(x)
tibble::tibble(x = c(".45", ".58*", ".68**"),
               y = c(1,2,3),
               z = 4:6) |>
               separate_star_column(x)

Prefix text with figure spaces to balance star text

Description

Prefix text with figure spaces to balance star text

Usage

star_balance(x, star = "\\*", superscript = TRUE)
star_balance(x, star = "\\*", superscript = TRUE)

Arguments

x

character vector

star

star text

superscript

Place superscript text if TRUE

Value

character vector

Examples


star_balance(".05\\^\\*\\*\\^")
star_balance(".05\\^\\*\\*\\^")

Like `stringr::str_wrap`, but attempts to create lines of equal width

Description

Like stringr::str_wrap, but attempts to create lines of equal width

Usage

str_wrap_equal(x, max_width = 30L, sep = "\n")
str_wrap_equal(x, max_width = 30L, sep = "\n")

Arguments

x

character

max_width

maximum line width

sep

separation character

Value

character

Examples

str_wrap_equal("This function attempts to split the string into lines with roughly equal width.")
str_wrap_equal("This function attempts to split the string into lines with roughly equal width.")

Surrounds text with tags unless empty

Description

Surrounds text with tags unless empty

Usage

tagger(x, tag = "<span>", right_tag = gsub("^<", "</", tag))

bold_md(x)

italic_md(x)

superscript_md(x)

subscript_md(x)

header_md(x, level = 1)
tagger(x, tag = "<span>", right_tag = gsub("^<", "</", tag))

bold_md(x)

italic_md(x)

superscript_md(x)

subscript_md(x)

header_md(x, level = 1)

Arguments

x

character vector

tag

opening tag, e.g., ⁠<span>⁠

right_tag

closing tag, e.g., ⁠</span>⁠. Defaults to the same value as the opening tag.

level

heading level

Value

character vector

Examples

x <- c("hello", "", NA)
tagger(x, "<span>")
bold_md(x)
italic_md(x)
superscript_md(x)
subscript_md(x)
header_md("Level 1")
header_md("Level 2", 2)
x <- c("hello", "", NA)
tagger(x, "<span>")
bold_md(x)
italic_md(x)
superscript_md(x)
subscript_md(x)
header_md("Level 1")
header_md("Level 2", 2)

Package 'apa7'

Help Index

Add break columns

Description

Usage

Arguments

Value

Examples

Make a column into a list column

Description

Usage

Arguments

Value

Examples

Adds stars next to a column based on p-values

Description

Usage

Arguments

Value

Examples

Align text on center text (default is decimal)

Description

Usage

Arguments

Value

Examples

Make contingency table with chi-square test of independence

Description

Usage

Arguments

Value

Examples

APA-formatted correlation table

Description

Usage

Arguments

Value

Examples

Convert data to flextable consistent with APA style

Description

Usage

Arguments

Details

Value

Examples

Format data columns

Description

Usage

Arguments

Value

Examples

print loadings

Description

Usage

Arguments

Value

Examples

p-value in APA format

Description

Usage

Arguments

Value

Examples

Make star notes for p-values

Description

Usage

Arguments

Value

Examples

format model parameters in APA style

Description

Usage

Arguments

Details

Value

Examples

format model performance metrics in APA style

Description

Usage

Arguments

Style `flextable::flextable` object according to APA style

Tables ready for `apa_flextable`