tests/testthat/test-apa.R
In dgromer/psymisc: Miscellaneous functions for psychologists
context("t_apa")
# Example data from Lakens, D. (2013). Calculating and reporting effect sizes to
# facilitate cumulative science: a practical primer for t-tests and ANOVAs.
# Frontiers in Psychology, 4, 863. doi:10.3389/fpsyg.2013.00863
df <- data.frame(movie_1 = c(9, 7, 8, 9, 8, 9, 9, 10, 9, 9),
movie_2 = c(9, 6, 7, 8, 7, 9, 8, 8, 8, 7))
test_that("Output for t_apa between subject", {
expect_match(t_apa(t_test(df$movie_1, df$movie_2, var.equal = TRUE),
print = FALSE),
"t\\(18\\) = 2\\.52, p = \\.022, d = 1\\.13")
})
test_that("Output for t_apa within subject", {
expect_match(t_apa(t_test(df$movie_1, df$movie_2, paired = TRUE),
print = FALSE),
"t\\(9\\) = 4\\.74, p = \\.001, d = 1\\.50")
})
test_that("Formal structure of t_apa output)", {
expect_match(t_apa(t_test(df$movie_1, df$movie_2, var.equal = TRUE),
print = FALSE),
paste0("t\\([[:digit:]]+\\) [=<] [[:digit:]]+\\.[[:digit:]]{2},",
" p [=<] \\.[[:digit:]]{3}, d [=<] [[:digit:]]+\\.",
"[[:digit:]]{2}"))
expect_match(t_apa(t_test(df$movie_1, df$movie_2), print = FALSE),
paste0("t\\([[:digit:]]+\\.[[:digit:]]{2}\\) [=<] ",
"[[:digit:]]+\\.[[:digit:]]{2}, p [=<] \\.[[:digit:]]{3}",
", d [=<] [[:digit:]]+\\.[[:digit:]]{2}"))
})
context("cor_apa")
# Example data from Hollander, M. & Wolfe, D. A. (1973). Nonparametric
# Statistical Methods. New York: John Wiley & Sons. Pages 185–194.
x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)
y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8)
test_that("Output for cor_apa", {
expect_match(cor_apa(cor.test(x, y, alternative = "greater"), print = FALSE),
"r\\(7)\\ = \\.57, p = \\.054")
expect_match(cor_apa(cor.test(x, y, method = "kendall",
alternative = "greater"), print = FALSE),
"r_tau = \\.44, p = \\.060")
expect_match(cor_apa(cor.test(x, y, method = "spearman",
alternative = "greater"), print = FALSE),
"r_s = \\.60, p = \\.048")
})
test_that("Formal structure of cor_apa output", {
expect_match(cor_apa(cor.test(x, y), print = FALSE),
paste0("r\\([[:digit:]]+\\) [=<] \\.[[:digit:]]{2}, p [=<] \\.",
"[[:digit:]]{3}"))
})
context("chisq_apa")
# Example data from Agresti, A. (2007) An Introduction to Categorical Data
# Analysis, 2nd ed., New York: John Wiley & Sons. Page 38.
m <- matrix(c(762, 327, 468, 484, 239, 477), nrow = 2)
dimnames(m) <- list(gender = c("F", "M"),
party = c("Democrat","Independent", "Republican"))
test_that("Output for chisq_apa", {
expect_match(chisq_apa(chisq.test(m), print = FALSE),
"chi\\^2\\(2\\) = 242\\.30, p < \\.001")
expect_match(chisq_apa(chisq.test(m), print_n = TRUE, print = FALSE),
"chi\\^2\\(2, n = 2757\\) = 242\\.30, p < \\.001")
})
test_that("Formal structure for chisq_apa output", {
expect_match(chisq_apa(chisq.test(m), print = FALSE),
paste0("chi\\^2\\([[:digit:]]+\\) = [[:digit:]]+\\.",
"[[:digit:]]{2}, p [=<] \\.[[:digit:]]{3}"))
})
context("anova_apa")
test_that("Formal structure for anova_apa output", {
library(ez)
data(ANT)
library(dplyr, warn.conflicts = FALSE)
data <-
ANT %>%
filter(error == 0) %>%
group_by(subnum, group, cue, flank) %>%
summarise(rt = mean(rt)) %>%
as.data.frame # ezANOVA does not support tbl_df
anova <- anova_apa(
ezANOVA(data, dv = rt, wid = subnum, within = c(cue, flank),
between = group, detailed = TRUE),
print = FALSE
)
# Intercept, three main effects, three two-way interactions, one three way
# interactions
expect_equal(nrow(anova), 1 + 3 + 3 + 1)
expect_match(`[.data.frame`(anova, anova$effect == "group", "text"),
paste0("F\\([[:digit:]]+, [[:digit:]]+\\) = [[:digit:]]+\\.",
"[[:digit:]]{2}, p [=<] \\.[[:digit:]]{3}, petasq ",
"[=<] \\.[[:digit:]]{2}"))
})
test_that("Output for anova_apa: oneway between ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 434.
data <- data.frame(id = factor(1:15),
dose = rep(c("placebo", "low dose", "high dose"),
each = 5),
libido = c(3, 2, 1, 1, 4, 5, 2, 4, 2, 3, 7, 4, 5, 3, 6))
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "libido", data = data, between = "dose"),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "dose",
"text"),
"F(2, 12) = 5.12, p = .025, petasq = .46")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = libido, wid = id, between = dose, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "dose", "text"),
"F(2, 12) = 5.12, p = .025, petasq = .46")
})
test_that("Output for anova_apa: factorial between ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 513f.
data <- data.frame(
id = factor(1:48),
gender = rep(c("female", "male"), each = 24),
alcohol = rep(c("none", "2 pints", "4 pints"), each = 8, times = 2),
attractiveness = c(65, 70, 60, 60, 60, 55, 60, 55, 70, 65, 60, 70, 65, 60,
60, 50, 55, 65, 70, 55, 55, 60, 50, 50, 50, 55, 80, 65,
70, 75, 75, 65, 45, 60, 85, 65, 70, 70, 80, 60, 30, 30,
30, 55, 35, 20, 45, 40)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "attractiveness", data = data,
between = c("gender", "alcohol")),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "gender",
"text"),
"F(1, 42) = 2.03, p = .161, petasq = .05")
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "alcohol",
"text"),
"F(2, 42) = 20.07, p < .001, petasq = .49")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "gender:alcohol",
"text"),
"F(2, 42) = 11.91, p < .001, petasq = .36")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = attractiveness, wid = id,
between = c(gender, alcohol), detailed = TRUE, type = 3),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "gender",
"text"),
"F(1, 42) = 2.03, p = .161, petasq = .05")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "alcohol",
"text"),
"F(2, 42) = 20.07, p < .001, petasq = .49")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "gender:alcohol",
"text"),
"F(2, 42) = 11.91, p < .001, petasq = .36")
})
test_that("Output for anova_apa: repeated-measures ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 513f.
data <- data.frame(
id = factor(rep(1:8, each = 4)),
animal = rep(c("stick insect", "kangaroo testicle", "fish eye",
"witchetty grub"), times = 8),
retch = c(8, 7, 1, 6, 9, 5, 2, 5, 6, 2, 3, 8, 5, 3, 1, 9, 8, 4, 5, 8, 7, 5,
6, 7, 10, 2, 7, 2, 12, 6, 8, 1)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "retch", data = data, within = "animal"),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "animal",
"text"),
"F(1.60, 11.19) = 3.79, p = .063, petasq = .35")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = retch, wid = id, within = animal, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "animal",
"text"),
"F(1.60, 11.19) = 3.79, p = .063, petasq = .35")
})
test_that("Output for anova_apa: factorial repeated-measures ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 583.
data <- data.frame(
id = factor(rep(1:20, each = 9)),
gender = rep(c("male", "female"), each = 10 * 9),
imagery = rep(c("positive", "negative", "neutral"), times = 60),
drink = rep(c("beer", "wine", "water"), each = 3, times = 20),
attitude = c(1, 6, 5, 38, -5, 4, 10, -14, -2, 43, 30, 8, 20, -12, 4, 9, -10,
-13, 15, 15, 12, 20, -15, 6, 6, -16, 1, 40, 30, 19, 28, -4, 0,
20, -10, 2, 8, 12, 8, 11, -2, 6, 27, 5, -5, 17, 17, 15, 17, -6,
6, 9, -6, -13, 30, 21, 21, 15, -2, 16, 19, -20, 3, 34, 23, 28,
27, -7, 7, 12, -12, 2, 34, 20, 26, 24, -10, 12, 12, -9, 4, 26,
27, 27, 23, -15, 14, 21, -6, 0, 1, -19, -10, 28, -13, 13, 33,
-2, 9, 7, -18, 6, 26, -16, 19, 23, -17, 5, 22, -8, 4, 34, -23,
14, 21, -19, 0, 30, -6, 3, 32, -22, 21, 17, -11, 4, 40, -6, 0,
24, -9, 19, 15, -10, 2, 15, -9, 4, 29, -18, 7, 13, -17, 8, 20,
-17, 9, 30, -17, 12, 16, -4, 10, 9, -12, -5, 24, -15, 18, 17,
-4, 8, 14, -11, 7, 34, -14, 20, 19, -1, 12, 15, -6, 13, 23,
-15, 15, 29, -1, 10)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "attitude", data = data,
within = c("drink", "imagery")),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "drink",
"text"),
"F(1.15, 21.93) = 5.11, p = .030, petasq = .21")
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "imagery",
"text"),
"F(1.49, 28.40) = 122.56, p < .001, petasq = .87")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "drink:imagery",
"text"),
"F(4, 76) = 17.15, p < .001, petasq = .47")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = attitude, wid = id, within = c(drink, imagery),
type = 3, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "drink", "text"),
"F(1.15, 21.93) = 5.11, p = .030, petasq = .21")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "imagery",
"text"),
"F(1.49, 28.40) = 122.56, p < .001, petasq = .87")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "drink:imagery",
"text"),
"F(4, 76) = 17.15, p < .001, petasq = .47")
})
test_that("Output for anova_apa: mixed ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 607.
data <- data.frame(
id = factor(rep(1:20, each = 9)),
gender = rep(c("male", "female"), each = 10 * 9),
looks = rep(c("attractive", "average", "ugly"), times = 60),
personality = rep(c("high carisma", "some charisma", "dullard"), each = 3,
times = 20),
rating = c(86, 84, 67, 88, 69, 50, 97, 48, 47, 91, 83, 53, 83, 74, 48, 86,
50, 46, 89, 88, 48, 99, 70, 48, 90, 45, 48, 89, 69, 58, 86, 77,
40, 87, 47, 53, 80, 81, 57, 88, 71, 50, 82, 50, 45, 80, 84, 51,
96, 63, 42, 92, 48, 43, 89, 85, 61, 87, 79, 44, 86, 50, 45, 100,
94, 56, 86, 71, 54, 84, 54, 47, 90, 74, 54, 92, 71, 58, 78, 38,
45, 89, 86, 63, 80, 73, 49, 91, 48, 39, 89, 91, 93, 88, 65, 54,
55, 48, 52, 84, 90, 85, 95, 70, 60, 50, 44, 45, 99, 100, 89, 80,
79, 53, 51, 48, 44, 86, 89, 83, 86, 74, 58, 52, 48, 47, 89, 87,
80, 83, 74, 43, 58, 50, 48, 80, 81, 79, 86, 59, 47, 51, 47, 40,
82, 92, 85, 81, 66, 47, 50, 45, 47, 97, 69, 87, 95, 72, 51, 45,
48, 46, 95, 92, 90, 98, 64, 53, 54, 53, 45, 95, 93, 96, 79, 66,
46, 52, 39, 47)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "rating", data = data,
between = "gender",
within = c("looks", "personality")),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "gender",
"text"),
"F(1, 18) = 0.00, p = .946, petasq < .01")
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "looks",
"text"),
"F(2, 36) = 423.73, p < .001, petasq = .96")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "personality", "text"),
"F(2, 36) = 328.25, p < .001, petasq = .95")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "gender:looks", "text"),
"F(2, 36) = 80.43, p < .001, petasq = .82")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "gender:personality",
"text"),
"F(2, 36) = 62.45, p < .001, petasq = .78")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "looks:personality",
"text"),
"F(4, 72) = 36.63, p < .001, petasq = .67")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = rating, wid = id, between = gender,
within = c(looks, personality), type = 3, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "gender",
"text"),
"F(1, 18) = 0.00, p = .946, petasq < .01")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "looks", "text"),
"F(2, 36) = 423.73, p < .001, petasq = .96")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "personality", "text"),
"F(2, 36) = 328.25, p < .001, petasq = .95")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "gender:looks", "text"),
"F(2, 36) = 80.43, p < .001, petasq = .82")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "gender:personality",
"text"),
"F(2, 36) = 62.45, p < .001, petasq = .78")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "looks:personality",
"text"),
"F(4, 72) = 36.63, p < .001, petasq = .67")
})
dgromer/psymisc documentation built on May 15, 2019, 7:22 a.m.
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context("t_apa")
# Example data from Lakens, D. (2013). Calculating and reporting effect sizes to
# facilitate cumulative science: a practical primer for t-tests and ANOVAs.
# Frontiers in Psychology, 4, 863. doi:10.3389/fpsyg.2013.00863
df <- data.frame(movie_1 = c(9, 7, 8, 9, 8, 9, 9, 10, 9, 9),
movie_2 = c(9, 6, 7, 8, 7, 9, 8, 8, 8, 7))
test_that("Output for t_apa between subject", {
expect_match(t_apa(t_test(df$movie_1, df$movie_2, var.equal = TRUE),
print = FALSE),
"t\\(18\\) = 2\\.52, p = \\.022, d = 1\\.13")
})
test_that("Output for t_apa within subject", {
expect_match(t_apa(t_test(df$movie_1, df$movie_2, paired = TRUE),
print = FALSE),
"t\\(9\\) = 4\\.74, p = \\.001, d = 1\\.50")
})
test_that("Formal structure of t_apa output)", {
expect_match(t_apa(t_test(df$movie_1, df$movie_2, var.equal = TRUE),
print = FALSE),
paste0("t\\([[:digit:]]+\\) [=<] [[:digit:]]+\\.[[:digit:]]{2},",
" p [=<] \\.[[:digit:]]{3}, d [=<] [[:digit:]]+\\.",
"[[:digit:]]{2}"))
expect_match(t_apa(t_test(df$movie_1, df$movie_2), print = FALSE),
paste0("t\\([[:digit:]]+\\.[[:digit:]]{2}\\) [=<] ",
"[[:digit:]]+\\.[[:digit:]]{2}, p [=<] \\.[[:digit:]]{3}",
", d [=<] [[:digit:]]+\\.[[:digit:]]{2}"))
})
context("cor_apa")
# Example data from Hollander, M. & Wolfe, D. A. (1973). Nonparametric
# Statistical Methods. New York: John Wiley & Sons. Pages 185–194.
x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)
y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8)
test_that("Output for cor_apa", {
expect_match(cor_apa(cor.test(x, y, alternative = "greater"), print = FALSE),
"r\\(7)\\ = \\.57, p = \\.054")
expect_match(cor_apa(cor.test(x, y, method = "kendall",
alternative = "greater"), print = FALSE),
"r_tau = \\.44, p = \\.060")
expect_match(cor_apa(cor.test(x, y, method = "spearman",
alternative = "greater"), print = FALSE),
"r_s = \\.60, p = \\.048")
})
test_that("Formal structure of cor_apa output", {
expect_match(cor_apa(cor.test(x, y), print = FALSE),
paste0("r\\([[:digit:]]+\\) [=<] \\.[[:digit:]]{2}, p [=<] \\.",
"[[:digit:]]{3}"))
})
context("chisq_apa")
# Example data from Agresti, A. (2007) An Introduction to Categorical Data
# Analysis, 2nd ed., New York: John Wiley & Sons. Page 38.
m <- matrix(c(762, 327, 468, 484, 239, 477), nrow = 2)
dimnames(m) <- list(gender = c("F", "M"),
party = c("Democrat","Independent", "Republican"))
test_that("Output for chisq_apa", {
expect_match(chisq_apa(chisq.test(m), print = FALSE),
"chi\\^2\\(2\\) = 242\\.30, p < \\.001")
expect_match(chisq_apa(chisq.test(m), print_n = TRUE, print = FALSE),
"chi\\^2\\(2, n = 2757\\) = 242\\.30, p < \\.001")
})
test_that("Formal structure for chisq_apa output", {
expect_match(chisq_apa(chisq.test(m), print = FALSE),
paste0("chi\\^2\\([[:digit:]]+\\) = [[:digit:]]+\\.",
"[[:digit:]]{2}, p [=<] \\.[[:digit:]]{3}"))
})
context("anova_apa")
test_that("Formal structure for anova_apa output", {
library(ez)
data(ANT)
library(dplyr, warn.conflicts = FALSE)
data <-
ANT %>%
filter(error == 0) %>%
group_by(subnum, group, cue, flank) %>%
summarise(rt = mean(rt)) %>%
as.data.frame # ezANOVA does not support tbl_df
anova <- anova_apa(
ezANOVA(data, dv = rt, wid = subnum, within = c(cue, flank),
between = group, detailed = TRUE),
print = FALSE
)
# Intercept, three main effects, three two-way interactions, one three way
# interactions
expect_equal(nrow(anova), 1 + 3 + 3 + 1)
expect_match(`[.data.frame`(anova, anova$effect == "group", "text"),
paste0("F\\([[:digit:]]+, [[:digit:]]+\\) = [[:digit:]]+\\.",
"[[:digit:]]{2}, p [=<] \\.[[:digit:]]{3}, petasq ",
"[=<] \\.[[:digit:]]{2}"))
})
test_that("Output for anova_apa: oneway between ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 434.
data <- data.frame(id = factor(1:15),
dose = rep(c("placebo", "low dose", "high dose"),
each = 5),
libido = c(3, 2, 1, 1, 4, 5, 2, 4, 2, 3, 7, 4, 5, 3, 6))
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "libido", data = data, between = "dose"),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "dose",
"text"),
"F(2, 12) = 5.12, p = .025, petasq = .46")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = libido, wid = id, between = dose, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "dose", "text"),
"F(2, 12) = 5.12, p = .025, petasq = .46")
})
test_that("Output for anova_apa: factorial between ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 513f.
data <- data.frame(
id = factor(1:48),
gender = rep(c("female", "male"), each = 24),
alcohol = rep(c("none", "2 pints", "4 pints"), each = 8, times = 2),
attractiveness = c(65, 70, 60, 60, 60, 55, 60, 55, 70, 65, 60, 70, 65, 60,
60, 50, 55, 65, 70, 55, 55, 60, 50, 50, 50, 55, 80, 65,
70, 75, 75, 65, 45, 60, 85, 65, 70, 70, 80, 60, 30, 30,
30, 55, 35, 20, 45, 40)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "attractiveness", data = data,
between = c("gender", "alcohol")),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "gender",
"text"),
"F(1, 42) = 2.03, p = .161, petasq = .05")
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "alcohol",
"text"),
"F(2, 42) = 20.07, p < .001, petasq = .49")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "gender:alcohol",
"text"),
"F(2, 42) = 11.91, p < .001, petasq = .36")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = attractiveness, wid = id,
between = c(gender, alcohol), detailed = TRUE, type = 3),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "gender",
"text"),
"F(1, 42) = 2.03, p = .161, petasq = .05")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "alcohol",
"text"),
"F(2, 42) = 20.07, p < .001, petasq = .49")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "gender:alcohol",
"text"),
"F(2, 42) = 11.91, p < .001, petasq = .36")
})
test_that("Output for anova_apa: repeated-measures ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 513f.
data <- data.frame(
id = factor(rep(1:8, each = 4)),
animal = rep(c("stick insect", "kangaroo testicle", "fish eye",
"witchetty grub"), times = 8),
retch = c(8, 7, 1, 6, 9, 5, 2, 5, 6, 2, 3, 8, 5, 3, 1, 9, 8, 4, 5, 8, 7, 5,
6, 7, 10, 2, 7, 2, 12, 6, 8, 1)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "retch", data = data, within = "animal"),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "animal",
"text"),
"F(1.60, 11.19) = 3.79, p = .063, petasq = .35")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = retch, wid = id, within = animal, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "animal",
"text"),
"F(1.60, 11.19) = 3.79, p = .063, petasq = .35")
})
test_that("Output for anova_apa: factorial repeated-measures ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 583.
data <- data.frame(
id = factor(rep(1:20, each = 9)),
gender = rep(c("male", "female"), each = 10 * 9),
imagery = rep(c("positive", "negative", "neutral"), times = 60),
drink = rep(c("beer", "wine", "water"), each = 3, times = 20),
attitude = c(1, 6, 5, 38, -5, 4, 10, -14, -2, 43, 30, 8, 20, -12, 4, 9, -10,
-13, 15, 15, 12, 20, -15, 6, 6, -16, 1, 40, 30, 19, 28, -4, 0,
20, -10, 2, 8, 12, 8, 11, -2, 6, 27, 5, -5, 17, 17, 15, 17, -6,
6, 9, -6, -13, 30, 21, 21, 15, -2, 16, 19, -20, 3, 34, 23, 28,
27, -7, 7, 12, -12, 2, 34, 20, 26, 24, -10, 12, 12, -9, 4, 26,
27, 27, 23, -15, 14, 21, -6, 0, 1, -19, -10, 28, -13, 13, 33,
-2, 9, 7, -18, 6, 26, -16, 19, 23, -17, 5, 22, -8, 4, 34, -23,
14, 21, -19, 0, 30, -6, 3, 32, -22, 21, 17, -11, 4, 40, -6, 0,
24, -9, 19, 15, -10, 2, 15, -9, 4, 29, -18, 7, 13, -17, 8, 20,
-17, 9, 30, -17, 12, 16, -4, 10, 9, -12, -5, 24, -15, 18, 17,
-4, 8, 14, -11, 7, 34, -14, 20, 19, -1, 12, 15, -6, 13, 23,
-15, 15, 29, -1, 10)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "attitude", data = data,
within = c("drink", "imagery")),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "drink",
"text"),
"F(1.15, 21.93) = 5.11, p = .030, petasq = .21")
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "imagery",
"text"),
"F(1.49, 28.40) = 122.56, p < .001, petasq = .87")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "drink:imagery",
"text"),
"F(4, 76) = 17.15, p < .001, petasq = .47")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = attitude, wid = id, within = c(drink, imagery),
type = 3, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "drink", "text"),
"F(1.15, 21.93) = 5.11, p = .030, petasq = .21")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "imagery",
"text"),
"F(1.49, 28.40) = 122.56, p < .001, petasq = .87")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "drink:imagery",
"text"),
"F(4, 76) = 17.15, p < .001, petasq = .47")
})
test_that("Output for anova_apa: mixed ANOVA", {
# Example data from Field, A., Miles, J. & Field, Z. (2012). Discovering
# statistics using R. London: Sage Publications. Page 607.
data <- data.frame(
id = factor(rep(1:20, each = 9)),
gender = rep(c("male", "female"), each = 10 * 9),
looks = rep(c("attractive", "average", "ugly"), times = 60),
personality = rep(c("high carisma", "some charisma", "dullard"), each = 3,
times = 20),
rating = c(86, 84, 67, 88, 69, 50, 97, 48, 47, 91, 83, 53, 83, 74, 48, 86,
50, 46, 89, 88, 48, 99, 70, 48, 90, 45, 48, 89, 69, 58, 86, 77,
40, 87, 47, 53, 80, 81, 57, 88, 71, 50, 82, 50, 45, 80, 84, 51,
96, 63, 42, 92, 48, 43, 89, 85, 61, 87, 79, 44, 86, 50, 45, 100,
94, 56, 86, 71, 54, 84, 54, 47, 90, 74, 54, 92, 71, 58, 78, 38,
45, 89, 86, 63, 80, 73, 49, 91, 48, 39, 89, 91, 93, 88, 65, 54,
55, 48, 52, 84, 90, 85, 95, 70, 60, 50, 44, 45, 99, 100, 89, 80,
79, 53, 51, 48, 44, 86, 89, 83, 86, 74, 58, 52, 48, 47, 89, 87,
80, 83, 74, 43, 58, 50, 48, 80, 81, 79, 86, 59, 47, 51, 47, 40,
82, 92, 85, 81, 66, 47, 50, 45, 47, 97, 69, 87, 95, 72, 51, 45,
48, 46, 95, 92, 90, 98, 64, 53, 54, 53, 45, 95, 93, 96, 79, 66,
46, 52, 39, 47)
)
# Build ANOVA with afex
anova_afex <- anova_apa(
afex::aov_ez(id = "id", dv = "rating", data = data,
between = "gender",
within = c("looks", "personality")),
print = FALSE
)
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "gender",
"text"),
"F(1, 18) = 0.00, p = .946, petasq < .01")
expect_identical(`[.data.frame`(anova_afex, anova_afex$effect == "looks",
"text"),
"F(2, 36) = 423.73, p < .001, petasq = .96")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "personality", "text"),
"F(2, 36) = 328.25, p < .001, petasq = .95")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "gender:looks", "text"),
"F(2, 36) = 80.43, p < .001, petasq = .82")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "gender:personality",
"text"),
"F(2, 36) = 62.45, p < .001, petasq = .78")
expect_identical(`[.data.frame`(anova_afex,
anova_afex$effect == "looks:personality",
"text"),
"F(4, 72) = 36.63, p < .001, petasq = .67")
# Build ANOVA with ez
anova_ez <- anova_apa(
ez::ezANOVA(data, dv = rating, wid = id, between = gender,
within = c(looks, personality), type = 3, detailed = TRUE),
print = FALSE
)
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "gender",
"text"),
"F(1, 18) = 0.00, p = .946, petasq < .01")
expect_identical(`[.data.frame`(anova_ez, anova_ez$effect == "looks", "text"),
"F(2, 36) = 423.73, p < .001, petasq = .96")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "personality", "text"),
"F(2, 36) = 328.25, p < .001, petasq = .95")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "gender:looks", "text"),
"F(2, 36) = 80.43, p < .001, petasq = .82")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "gender:personality",
"text"),
"F(2, 36) = 62.45, p < .001, petasq = .78")
expect_identical(`[.data.frame`(anova_ez,
anova_ez$effect == "looks:personality",
"text"),
"F(4, 72) = 36.63, p < .001, petasq = .67")
})
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