Creates an ANOVA table in APA style based on output of aov_ez command from afex package

Usage

apa.afex.table(
  afex.output,
  correction = "GG",
  table.title = "",
  filename,
  table.number = 0
)

Arguments

afex.output: Output object from afex::aov_ez() command (class afex_aov)
correction: Type of sphericity correction: "none", "GG", or "HF" corresponding to none, Greenhouse-Geisser and Huynh-Feldt, respectively.
table.title: String containing text for table title
filename: (optional) Output filename document filename (must end in .rtf or .doc only)
table.number: Integer to use in table number output line

Value

APA table object

Examples

if  (requireNamespace("afex", quietly = TRUE)){
if  (requireNamespace("apaTables", quietly = TRUE)){
if  (requireNamespace("tidyr", quietly = TRUE)){


#
# ** Example 1: Between Participant Predictors
#

goggles <- apaTables::goggles

goggles_results <- afex::aov_ez(id = "participant", dv = "attractiveness",
                                 data = goggles,
                                 between = c("gender", "alcohol"))


# Make APA table - save after all 3 examples
goggles_table <- apa.afex.table(afex.output = goggles_results)

# Create a table for your PDF
# Include the lines below in your rmarkdown or Quarto document
apa.knit.table.for.pdf(table_object = goggles_table)


# \donttest{
#
# ** Example 2: Within Participant Predictors
#

drink_attitude_wide <- apaTables::drink_attitude_wide

# Convert data from wide format to long format where one row represents one OBSERVATION.
# Wide format column names MUST represent levels of each variable separated by an underscore.
# See vignette for further details.

drink_attitude_long <- tidyr::pivot_longer(drink_attitude_wide,
                              cols = beer_positive:water_neutral,
                             names_to = c("drink", "imagery"),
                             names_sep = "_",
                              values_to = "attitude")


drink_attitude_long$drink <- as.factor(drink_attitude_long$drink)
drink_attitude_long$imagery <- as.factor(drink_attitude_long$imagery)


drink_attitude_results <- afex::aov_ez(id = "participant", dv = "attitude",
                             data = drink_attitude_long,
                             within = c("drink", "imagery"))


# Make APA table - save after all 3 examples
drink_table <- apa.afex.table(afex.output = drink_attitude_results)

# Create a table for your PDF
# Include the lines below in your rmarkdown or Quarto document
apa.knit.table.for.pdf(table_object = drink_table)


#
# ** Example 3: Between and Within Participant Predictors
#

dating_wide <- apaTables::dating_wide

# Convert data from wide format to long format where one row represents one OBSERVATION.
# Wide format column names MUST represent levels of each variable separated by an underscore.
# See vignette for further details.


dating_long <- tidyr::pivot_longer(dating_wide,
                              cols = attractive_high:ugly_none,
                             names_to = c("looks", "personality"),
                             names_sep = "_",
                              values_to = "date_rating")
#'
dating_long$looks <- as.factor(dating_long$looks)
dating_long$personality <- as.factor(dating_long$personality)


dating_results <- afex::aov_ez(id = "participant", dv = "date_rating",
                                data = dating_long,
                                between = "gender",
                                within = c("looks", "personality"))


# Make APA table - save after all 3 examples
dating_table <- apa.afex.table(afex.output = dating_results)

# Create a table for your PDF
# Include the lines below in your rmarkdown or Quarto document
apa.knit.table.for.pdf(table_object = dating_table)


#
# Saving all three tables
#
apa.save(filename = file.path(tempdir(), "tables_afex.doc"),
                goggles_table,
                 drink_table,
                dating_table)

# delete demo file
unlink(file.path(tempdir(), "tables_afex.doc"))
# }
}}}
#> Contrasts set to contr.sum for the following variables: gender, alcohol
#> Contrasts set to contr.sum for the following variables: gender
#> Warning: HF eps > 1 treated as 1