styler

R/effectsize.R

@@ -51,8 +51,10 @@
 #' Tt <- t.test(1:10, y = c(7:20), alternative = "less")
 #' effectsize(Tt)
 #'
-#' sleep2 <- reshape(sleep, direction = "wide",
-#'                   idvar = "ID", timevar = "group")
+#' sleep2 <- reshape(sleep,
+#'   direction = "wide",
+#'   idvar = "ID", timevar = "group"
+#' )
 #' Tt <- t.test(sleep2$extra.1, sleep2$extra.2, paired = TRUE)
 #' effectsize(Tt, type = "rm_b")
 #'

R/repeated_measures_d.R

@@ -106,8 +106,10 @@
 #' # Paired data -------
 #'
 #' data("sleep")
-#' sleep2 <- reshape(sleep, direction = "wide",
-#'                   idvar = "ID", timevar = "group")
+#' sleep2 <- reshape(sleep,
+#'   direction = "wide",
+#'   idvar = "ID", timevar = "group"
+#' )
 #'
 #' repeated_measures_d(Pair(extra.1, extra.2) ~ 1, data = sleep2)
 #'
@@ -204,9 +206,10 @@ repeated_measures_d <- function(x, y,
 
   # rename column to method
   colnames(out)[1] <- switch(method,
-                             d = "Cohens_d",
-                             b = "Beckers_d",
-                             paste0("d_", method))
+    d = "Cohens_d",
+    b = "Beckers_d",
+    paste0("d_", method)
+  )
 
   class(out) <- c("effectsize_difference", "effectsize_table", "see_effectsize_table", class(out))
   .someattributes(out) <- .nlist(
@@ -237,7 +240,7 @@ rm_d <- repeated_measures_d
     d <- (m - mu) / s
 
     # Cooper et al., 2009, eq 12.21
-    se <- sqrt(((1 / n) + (d ^ 2) / (2 * n)) * f)
+    se <- sqrt(((1 / n) + (d^2) / (2 * n)) * f)
   } else if (method == "av") {
     s <- sqrt((stats::var(x) + stats::var(y)) / 2)
     d <- (m - mu) / s
@@ -249,13 +252,13 @@ rm_d <- repeated_measures_d
     d <- (m - mu) / s
 
     # Hedges and Olkin, 1985, page 86, eq 14
-    se <- sqrt((1 / n) + (d ^ 2) / (2 * n))
+    se <- sqrt((1 / n) + (d^2) / (2 * n))
   } else if (method == "b") {
     s <- stats::sd(y)
     d <- (m - mu) / s
 
     # Becker 1988, eq. 6
-    se <- sqrt((2 * (1 - r) / n) + (d ^ 2) / (2 * n))
+    se <- sqrt((2 * (1 - r) / n) + (d^2) / (2 * n))
   }
 
   .nlist(d, se, df)
@@ -270,27 +273,29 @@ rm_d <- repeated_measures_d
   }
 
   mod <- suppressWarnings(
-    stats::aov(y ~ condition + Error(id / condition), data = data,
-               contrasts = list(condition = contr.treatment))
+    stats::aov(y ~ condition + Error(id / condition),
+      data = data,
+      contrasts = list(condition = contr.treatment)
+    )
   )
   m <- -unname(coef(mod[["id:condition"]]))
   m_V <- unname(vcov(mod[["id:condition"]])[1])
 
   pars <- parameters::model_parameters(mod)
 
   if (method == "d") {
-    e <- as.data.frame(pars[pars$Parameter == "Residuals",])
+    e <- as.data.frame(pars[pars$Parameter == "Residuals", ])
   } else if (method == "r") {
-    e <- as.data.frame(pars[pars$Group == "Within",])
+    e <- as.data.frame(pars[pars$Group == "Within", ])
   }
 
   s <- sqrt(sum(e[["Sum_Squares"]]) / sum(e[["df"]]))
   df <- sum(e[["df"]])
 
   d <- (m - mu) / s
   se <- sqrt(
-    (df / (df - 2)) * (m_V / (s ^ 2)) +
-      (d ^ 2) * (8 * df ^ 2 - df + 2) / (16 * (df - 2) * ((df - 1) ^ 2))
+    (df / (df - 2)) * (m_V / (s^2)) +
+      (d^2) * (8 * df^2 - df + 2) / (16 * (df - 2) * ((df - 1)^2))
   )
 
   .nlist(d, se, df)

R/utils_validate_input_data.R

@@ -135,8 +135,8 @@
       }
 
       mf <- tapply(mf[[1]], mf[3:2], mean, na.rm = TRUE)
-      x <- mf[,1]
-      y <- mf[,2]
+      x <- mf[, 1]
+      y <- mf[, 2]
     } else if (x[[2]][[1]] == as.name("Pair")) {
       # is Pair (wide)
       mf <- .resolve_formula(x, data, ...)

data-raw/df data.R

@@ -251,10 +251,11 @@ save(hardlyworking, file = "data/hardlyworking.rdata")
 # rouder2016 --------------------------------------------------------------
 
 rouder2016 <- read.table("data-raw/effectSizePuzzler.txt",
-                         header = TRUE, stringsAsFactors = FALSE)
+  header = TRUE, stringsAsFactors = FALSE
+)
 rouder2016[["id"]] <- factor(rouder2016[["id"]])
 rouder2016[["cond"]] <- factor(rouder2016[["cond"]])
 
 save(rouder2016, file = "data/rouder2016.rdata")
 
-# styler: on
+# styler: on

data-raw/es_info.R

@@ -4,13 +4,11 @@ es_info <- tibble::tribble(
   "Cohens_d", "Cohen's d", NA, "twotail", -Inf, Inf, 0,
   "Hedges_g", "Hedges' g", NA, "twotail", -Inf, Inf, 0,
   "Glass_delta", "Glass' delta", "Glass' \u0394", "twotail", -Inf, Inf, 0,
-
   "d_rm", "d (rm)", "d\u1D63\u2098", "twotail", -Inf, Inf, 0,
   "d_av", "d (av)", "d\u2090\u1D65", "twotail", -Inf, Inf, 0,
   "d_z", "d (z)", NA, "twotail", -Inf, Inf, 0,
   "Beckers_d", "Becker's d", NA, "twotail", -Inf, Inf, 0,
   "d_r", "d (r)", "d\u1D63", "twotail", -Inf, Inf, 0,
-
   "Mahalanobis_D", "Mahalanobis' D", NA, "onetail", 0, Inf, 0,
   "Means_ratio", "Means Ratio", NA, "twotail", 0, Inf, 1,
   "Means_ratio_adjusted", "Means Ratio (adj.)", NA, "twotail", 0, Inf, 1,

tests/testthat/test-effectsize.R

@@ -45,8 +45,10 @@ test_that("t-test", {
   model <- t.test(x, y, paired = TRUE)
   expect_equal(effectsize(model, verbose = FALSE), cohens_d(x, y, paired = TRUE, verbose = FALSE), ignore_attr = TRUE)
 
-  sleep2 <<- reshape(sleep, direction = "wide",
-                     idvar = "ID", timevar = "group")
+  sleep2 <<- reshape(sleep,
+    direction = "wide",
+    idvar = "ID", timevar = "group"
+  )
   tt <- t.test(sleep2$extra.1, sleep2$extra.2, paired = TRUE)
 
   es1 <- effectsize(tt, type = "rm_b")

tests/testthat/test-rm_d.R

@@ -1,19 +1,22 @@
 test_that("rm_d | paired data", {
-
   data("sleep")
-  sleep2 <- reshape(sleep, direction = "wide",
-                    idvar = "ID", timevar = "group")
+  sleep2 <- reshape(sleep,
+    direction = "wide",
+    idvar = "ID", timevar = "group"
+  )
 
-  d1 <- rm_d(sleep$extra[sleep$group==1],
-             sleep$extra[sleep$group==2])
+  d1 <- rm_d(
+    sleep$extra[sleep$group == 1],
+    sleep$extra[sleep$group == 2]
+  )
   d2 <- rm_d(Pair(extra.1, extra.2) ~ 1, data = sleep2)
   expect_no_message(d3 <- rm_d(extra ~ group | ID, data = sleep))
 
   expect_equal(d1, d2)
   expect_equal(d1, d3)
 
   d_z <- rm_d(Pair(extra.1, extra.2) ~ 1, data = sleep2, method = "z")
-  d_z2 <- hedges_g(sleep$extra[sleep$group==1] - sleep$extra[sleep$group==2])
+  d_z2 <- hedges_g(sleep$extra[sleep$group == 1] - sleep$extra[sleep$group == 2])
 
   expect_equal(d_z[[1]], d_z2[[1]])
   expect_equal(d_z$CI_low, d_z2$CI_low, tolerance = 0.01)
@@ -27,14 +30,18 @@ test_that("rm_d | paired data", {
 
   # equal with equal variance:
   dat <- data.frame(
-    V1 = c(-0.32150435528124, -4.02978032779713, 0.159645811226589,
-           1.95179927058772, 0.168527299289471, 3.4499229496418,
-           -1.87888939495506, 0.431333839911973, -0.26004200470096,
-           0.328986912076835),
-    V2 = c(2.50107579495566, -0.32926747002329, 4.01118960037018,
-           1.44969284040984, -1.46241877172319, 1.25068499614667,
-           0.028928469929524, 3.05532100575796, -1.67014771817319,
-           3.16494125234984)
+    V1 = c(
+      -0.32150435528124, -4.02978032779713, 0.159645811226589,
+      1.95179927058772, 0.168527299289471, 3.4499229496418,
+      -1.87888939495506, 0.431333839911973, -0.26004200470096,
+      0.328986912076835
+    ),
+    V2 = c(
+      2.50107579495566, -0.32926747002329, 4.01118960037018,
+      1.44969284040984, -1.46241877172319, 1.25068499614667,
+      0.028928469929524, 3.05532100575796, -1.67014771817319,
+      3.16494125234984
+    )
   )
 
   d_rm <- rm_d("V1", "V2", data = dat, adjust = FALSE)
@@ -61,21 +68,29 @@ test_that("rm_d | replication data", {
     rm_d(rt ~ cond | id, data = rouder2016, method = "d"),
   )
 
-  d_av <- rm_d(rt ~ cond | id, data = rouder2016, method = "av",
-               adjust = FALSE, verbose = FALSE)
-  d_z <- rm_d(rt ~ cond | id, data = rouder2016, method = "z",
-              adjust = FALSE, verbose = FALSE)
-  d_d <- rm_d(rt ~ cond | id, data = rouder2016, method = "d",
-              adjust = FALSE)
-  d_r <- rm_d(rt ~ cond | id, data = rouder2016, method = "r",
-              adjust = FALSE)
+  d_av <- rm_d(rt ~ cond | id,
+    data = rouder2016, method = "av",
+    adjust = FALSE, verbose = FALSE
+  )
+  d_z <- rm_d(rt ~ cond | id,
+    data = rouder2016, method = "z",
+    adjust = FALSE, verbose = FALSE
+  )
+  d_d <- rm_d(rt ~ cond | id,
+    data = rouder2016, method = "d",
+    adjust = FALSE
+  )
+  d_r <- rm_d(rt ~ cond | id,
+    data = rouder2016, method = "r",
+    adjust = FALSE
+  )
 
   # values takes from
   # https://jakewestfall.org/blog/index.php/2016/03/25/five-different-cohens-d-statistics-for-within-subject-designs/
   expect_equal(d_av[[1]], -0.8357347, tolerance = 0.001)
   expect_equal(d_z[[1]], -1.353713, tolerance = 0.001)
   expect_equal(d_d[[1]], -0.2497971, tolerance = 0.001)
-  expect_equal(d_r[[1]], -0.052298/0.20195, tolerance = 0.001)
+  expect_equal(d_r[[1]], -0.052298 / 0.20195, tolerance = 0.001)
 
   # also:
   expect_equal(d_d[[1]], cohens_d(rt ~ cond, data = rouder2016)[[1]], tolerance = 0.001)