Creates an ANOVA table in APA style based output of ezANOVA command from ez package

Usage

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

Arguments

ez.output: Output object from ezANOVA command from ez package
correction: Type of sphercity 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("ez", quietly = TRUE)){
if  (requireNamespace("apaTables", quietly = TRUE)){
if  (requireNamespace("tidyr", quietly = TRUE)){


#
# ** Example 1: Between Participant Predictors
#

goggles <- apaTables::goggles

# Use ezANOVA
# Be sure use the options command, as below, to ensure sufficient digits

options(digits = 10)
goggles_results <- ez::ezANOVA(data = goggles,
                          dv = attractiveness,
                          between = .(gender, alcohol),
                          participant ,
                          detailed = TRUE)


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

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


#
# ** 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)


# Set contrasts to match Field et al. (2012) textbook output

alcohol_vs_water <- c(1, 1, -2)
beer_vs_wine <- c(-1, 1, 0)
negative_vs_other <- c(1, -2, 1)
positive_vs_neutral <- c(-1, 0, 1)
contrasts(drink_attitude_long$drink) <- cbind(alcohol_vs_water, beer_vs_wine)
contrasts(drink_attitude_long$imagery) <- cbind(negative_vs_other, positive_vs_neutral)


# Use ezANOVA
# Be sure use the options command, as below, to ensure sufficient digits

options(digits = 10)
drink_attitude_results <- ez::ezANOVA(data = drink_attitude_long,
                   dv = .(attitude), wid = .(participant),
                   within = .(drink, imagery),
                   type = 3, detailed = TRUE)


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

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


# Set contrasts to match Field et al. (2012) textbook output

some_vs_none <- c(1, 1, -2)
hi_vs_av <- c(1, -1, 0)
attractive_vs_ugly <- c(1, 1, -2)
attractive_vs_average <- c(1, -1, 0)
contrasts(dating_long$personality) <- cbind(some_vs_none, hi_vs_av)
contrasts(dating_long$looks) <- cbind(attractive_vs_ugly, attractive_vs_average)


# Use ezANOVA

options(digits = 10)
dating_results <-ez::ezANOVA(data = dating_long, dv = .(date_rating),
                         wid = .(participant),
                         between = .(gender),
                         within = .(looks, personality),
                         type = 3, detailed = TRUE)


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

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


#
# Saving all three tables
#
apa.save("tables_ezANOVA.doc",
                goggles_table,
                 drink_table,
                dating_table)

# delete demo file
if (file.exists("tables_ezANOVA.doc")) {
     file.remove("tables_ezANOVA.doc")
}
}}}
#> Coefficient covariances computed by hccm()
#> [1] TRUE