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,
  ...
)

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")])
Variable M SD 1 2 3 4 
1.  mpg 20.09 6.03 — 
2.  am  0.41 0.50 .60 *** — 
3.  gear  3.69 0.74 .48 ** .79 *** — 
4.  carb  2.81 1.62 −.55 ** .06 .27 — 
** p < .01. *** p < .001
apa_cor(mtcars[, c("mpg", "am", "gear", "carb")],
        output = "tibble",
        star_significant = FALSE)
#> # A tibble: 4 × 8
#>   apa7listcolumn Variable M     SD    `1`   `2`   `3`   `4`  
#>   <chr>          <chr>    <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 1.             mpg      20.09 6.03  —     NA    NA    NA   
#> 2 2.             am       0.41  0.50  .60   —     NA    NA   
#> 3 3.             gear     3.69  0.74  .48   .79   —     NA   
#> 4 4.             carb     2.81  1.62  −.55  .06   .27   —

Variable		M	SD	1		2		3	4
1.	mpg	20.09	6.03	—
2.	am	0.41	0.50	.60	***	—
3.	gear	3.69	0.74	.48	**	.79	***	—
4.	carb	2.81	1.62	−.55	**	.06		.27	—
p < .01. * p < .001