easystats · IndrajeetPatil · Sep 20, 2023 · Sep 20, 2023 · Sep 20, 2023 · Sep 20, 2023
diff --git a/NAMESPACE b/NAMESPACE
@@ -247,14 +247,8 @@ importFrom(bayestestR,equivalence_test)
 importFrom(datawizard,standardise)
 importFrom(datawizard,standardize)
 importFrom(insight,display)
-importFrom(insight,find_predictors)
 importFrom(insight,print_html)
 importFrom(insight,print_md)
-importFrom(parameters,model_parameters)
 importFrom(parameters,standardize_info)
 importFrom(parameters,standardize_parameters)
 importFrom(parameters,standardize_posteriors)
-importFrom(stats,anova)
-importFrom(stats,aov)
-importFrom(stats,na.omit)
-importFrom(utils,packageVersion)
diff --git a/R/cohens_d.R b/R/cohens_d.R
@@ -266,7 +266,7 @@ glass_delta <- function(x, y = NULL, data = NULL,
   }
 
   out <- data.frame(d = (d - mu) / s)
-  types <- c("d" = "Cohens_d", "g" = "Hedges_g", "delta" = "Glass_delta")
+  types <- c(d = "Cohens_d", g = "Hedges_g", delta = "Glass_delta")
   colnames(out) <- types[type]
 
   if (.test_ci(ci)) {

diff --git a/R/convert_stat_chisq.R b/R/convert_stat_chisq.R
@@ -30,13 +30,13 @@
 #' \ifelse{latex}{
 #' \deqn{\textrm{Cramer's } V = \phi / \sqrt{\min(\textit{nrow}, \textit{ncol}) - 1}}
 #' }{
 #' \deqn{\textrm{Cramer's } V = \phi / \sqrt{\min(\textit{nrow}, \textit{ncol}) - 1}}{Cramer's V = \phi / sqrt(min(nrow, ncol) - 1)}
 #' }
 #'
 #' \ifelse{latex}{
 #' \deqn{\textrm{Tschuprow's } T = \phi / \sqrt[4]{(\textit{nrow} - 1) \times (\textit{ncol} - 1)}}
 #' }{
 #' \deqn{\textrm{Tschuprow's } T = \phi / \sqrt[4]{(\textit{nrow} - 1) \times (\textit{ncol} - 1)}}{Tschuprow's T = \phi / sqrt(sqrt((nrow-1) * (ncol-1)))}
 #' }
 #'
 #' \ifelse{latex}{
@@ -48,7 +48,8 @@
 #'
 #' \deqn{\textrm{Pearson's } C = \sqrt{\chi^2 / (\chi^2 + n)}}{Pearson's C = sqrt(\chi^2 / (\chi^2 + n))}
 #'
-#' For versions adjusted for small-sample bias of \eqn{\phi}, \eqn{V}, and \eqn{T}, see [Bergsma, 2013](https://en.wikipedia.org/wiki/Cram%C3%A9r%27s_V#Bias_correction).
+#' For versions adjusted for small-sample bias of \eqn{\phi}, \eqn{V}, and \eqn{T},
+#' see [Bergsma, 2013](https://en.wikipedia.org/wiki/Cram%C3%A9r%27s_V#Bias_correction).
 #'
 #' @inheritSection effectsize_CIs Confidence (Compatibility) Intervals (CIs)
 #' @inheritSection effectsize_CIs CIs and Significance Tests

diff --git a/R/effectsize-package.R b/R/effectsize-package.R
@@ -18,8 +18,9 @@
 #' and hypothesis tests, such as [cohens_d()], [phi()], [eta_squared()], and
 #' many more.
 #'
-#' See [`vignette("effectsize", package = "effectsize")`](https://easystats.github.io/effectsize/articles/effectsize.html) for more details,
-#' or [`vignette(package = "effectsize")`](https://easystats.github.io/effectsize/articles/) for a full list of vignettes.
+#' See [`vignette("effectsize", package = "effectsize")`](https://easystats.github.io/effectsize/articles/effectsize.html)
+#' for more details, or [`vignette(package = "effectsize")`](https://easystats.github.io/effectsize/articles/)
+#' for a full list of vignettes.
 #'
 #' References: Ben-Shachar et al. (2020) \doi{10.21105/joss.02815}.
 #'

diff --git a/R/eta_squared-main.R b/R/eta_squared-main.R
@@ -23,7 +23,7 @@
 #' @param verbose Toggle warnings and messages on or off.
 #' @inheritParams chisq_to_phi
 #' @param ... Arguments passed to or from other methods.
 #'   - Can be `include_intercept = TRUE` to include the effect size for the intercept (when it is included in the ANOVA table).
 #'   - For Bayesian models, arguments passed to `ss_function`.
 #'
 #' @return
@@ -248,7 +248,7 @@
                            ci = 0.95, alternative = "greater",
                            verbose = TRUE, ...) {
  alternative <- .match.alt(alternative, FALSE)
  out <- .anova_es(model, type = "epsilon", partial = partial, ci = ci, alternative = alternative, verbose = verbose, ...)
  class(out) <- unique(c("effectsize_anova", "effectsize_table", "see_effectsize_table", class(out)))
  if ("CI" %in% colnames(out)) attr(out, "ci_method") <- list(method = "ncp", distribution = "F")
  attr(out, "approximate") <- isTRUE(attr(out, "approximate", exact = TRUE))
@@ -294,7 +294,7 @@

  es_name <- get_effectsize_name(colnames(res))
  res[[es_name]] <- res[[es_name]] / (1 - res[[es_name]])
  if (grepl("_partial", es_name)) {
    colnames(res)[colnames(res) == es_name] <- "Cohens_f2_partial"
  } else {
    colnames(res)[colnames(res) == es_name] <- "Cohens_f2"
@@ -316,7 +316,7 @@
  if ("CI" %in% colnames(res)) attr(res, "ci_method") <- list(method = "ncp", distribution = "F")
  class(res) <- unique(c("effectsize_anova", "effectsize_table", "see_effectsize_table", class(res)))
  attr(res, "approximate") <- isTRUE(attr(res, "approximate", exact = TRUE))
  attr(res, "table_footer") <- if (method != "eta") sprintf("Based on %s squared.", paste0(toupper(substring(method, 1, 1)), substring(method, 2)))
  res
 }

@@ -448,7 +448,7 @@

      aov_table$Eta2_generalized <- aov_table$Sum_Squares /
        (aov_table$Sum_Squares + values$Sum_Squares_residuals + obs_SSn1 - obs_SSn2)
    } else if (!isTRUE(partial)) {
      aov_table$Eta2 <- aov_table$Sum_Squares /
        values$Sum_Squares_total
    } else {
@@ -457,7 +457,7 @@
          (aov_table$Sum_Squares + values$Sum_Squares_residuals)
    }
  } else if (type == "omega") {
    if (!isTRUE(partial)) {
      aov_table$Omega2 <-
        (aov_table$Sum_Squares - aov_table$df * values$Mean_Square_residuals) /
          (values$Sum_Squares_total + values$Mean_Square_residuals)
@@ -469,7 +469,7 @@
      aov_table$Omega2_partial <- pmax(0, aov_table$Omega2_partial)
    }
  } else if (type == "epsilon") {
    if (!isTRUE(partial)) {
      aov_table$Epsilon2 <-
        (aov_table$Sum_Squares - aov_table$df * values$Mean_Square_residuals) /
          values$Sum_Squares_total
@@ -764,7 +764,6 @@
 
 
 #' @keywords internal
-#' @importFrom stats anova
 .anova_es.default <- function(model, ...) {
   .anova_es.anova(stats::anova(model), ...)
 }
@@ -842,8 +841,6 @@
 }
 
 #' @keywords internal
-#' @importFrom parameters model_parameters
-#' @importFrom stats anova
 .anova_es.aov <- function(model,
                           type = c("eta", "omega", "epsilon"),
                           partial = TRUE,
@@ -885,8 +882,6 @@
 .anova_es.glm <- .anova_es.lm
 
 #' @keywords internal
-#' @importFrom parameters model_parameters
-#' @importFrom insight find_predictors
 .anova_es.aovlist <- function(model,
                               type = c("eta", "omega", "epsilon"),
                               partial = TRUE,

diff --git a/R/eta_squared-methods.R b/R/eta_squared-methods.R
@@ -110,7 +110,7 @@
     within <- names(model$idata)
     within <- lapply(within, function(x) c(NA, x))
     within <- do.call(expand.grid, within)
-    within <- apply(within, 1, na.omit)
+    within <- apply(within, 1, stats::na.omit)
     ns <- sapply(within, length)
     within <- sapply(within, paste, collapse = ":")
     within <- within[order(ns)]
@@ -179,7 +179,6 @@
 #' @keywords internal
 .anova_es.anova.lme <- .anova_es.anova
 
-#' @importFrom stats na.omit
 #' @keywords internal
 .anova_es.parameters_model <- function(model,
                                        type = c("eta", "omega", "epsilon"),
@@ -249,8 +248,6 @@
 # Specific models ---------------------------------------------------------
 
 #' @keywords internal
-#' @importFrom stats aov
-#' @importFrom utils packageVersion
 .anova_es.maov <- function(model,
                            type = c("eta", "omega", "epsilon"),
                            partial = TRUE,

diff --git a/R/xtab_diff.R b/R/xtab_diff.R
@@ -295,7 +295,7 @@ arr <- function(x, y = NULL, ci = 0.95, alternative = "two.sided", ...) {
 nnt <- function(x, y = NULL, ci = 0.95, alternative = "two.sided", ...) {
   alternative <- .match.alt(alternative)
 
-  flip_alt <- c("less" = "greater", "greater" = "less", "two.sided" = "two.sided")
+  flip_alt <- c(less = "greater", greater = "less", two.sided = "two.sided")
   alternative2 <- unname(flip_alt[alternative])
 
   if (.is_htest_of_type(x, "Pearson's Chi-squared", "Chi-squared-test")) {

diff --git a/man/convert_chisq.Rd b/man/convert_chisq.Rd
diff --git a/man/effectsize-package.Rd b/man/effectsize-package.Rd
diff --git a/tests/testthat/test-effectsize.R b/tests/testthat/test-effectsize.R
@@ -252,14 +252,56 @@ test_that("htest | rank", {
 })
 
 test_that("htest | Get args from htest", {
-  tt <- t.test(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3, conf.level = 0.8, var.equal = TRUE)
-  expect_equal(cohens_d(tt), cohens_d(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3, ci = 0.8), ignore_attr = TRUE)
+  tt <- t.test(
+    mtcars$hp,
+    mtcars$mpg,
+    alternative = "l",
+    mu = -3,
+    conf.level = 0.8,
+    var.equal = TRUE
+  )
+  expect_equal(
+    cohens_d(tt),
+    cohens_d(
+      mtcars$hp,
+      mtcars$mpg,
+      alternative = "l",
+      mu = -3,
+      ci = 0.8
+    ),
+    ignore_attr = TRUE
+  )
 
-  suppressWarnings(ww1 <- wilcox.test(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3))
-  expect_equal(rank_biserial(ww1), rank_biserial(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3), ignore_attr = TRUE)
+  suppressWarnings({
+    ww1 <- wilcox.test(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3)
+  })
+  expect_equal(
+    rank_biserial(ww1),
+    rank_biserial(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3),
+    ignore_attr = TRUE
+  )
 
-  suppressWarnings(ww2 <- wilcox.test(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3, conf.int = TRUE, conf.level = 0.8))
-  expect_equal(rank_biserial(ww2), rank_biserial(mtcars$hp, mtcars$mpg, alternative = "l", mu = -3, ci = 0.8), ignore_attr = TRUE)
+  suppressWarnings({
+    ww2 <- wilcox.test(
+      mtcars$hp,
+      mtcars$mpg,
+      alternative = "l",
+      mu = -3,
+      conf.int = TRUE,
+      conf.level = 0.8
+    )
+  })
+  expect_equal(
+    rank_biserial(ww2),
+    rank_biserial(
+      mtcars$hp,
+      mtcars$mpg,
+      alternative = "l",
+      mu = -3,
+      ci = 0.8
+    ),
+    ignore_attr = TRUE
+  )
 })
 
 

diff --git a/tests/testthat/test-eta_squared.R b/tests/testthat/test-eta_squared.R
@@ -516,19 +516,47 @@ test_that("afex | mixed()", {
   # Intercept
   data("stroop", package = "afex")
   stroop <- subset(stroop, study == 1 & acc == 1 & trialnum < 20)
-  suppressMessages(m1 <- afex::mixed(rt ~ condition + (condition | pno), data = stroop, method = "KR"))
-  suppressMessages(m2 <- afex::mixed(rt ~ condition + (condition | pno), data = stroop, test_intercept = TRUE, method = "KR"))
+  suppressMessages({
+    m1 <- afex::mixed(rt ~ condition + (condition | pno), data = stroop, method = "KR")
+  })
+  suppressMessages({
+    m2 <- afex::mixed(rt ~ condition + (condition | pno),
+      data = stroop,
+      test_intercept = TRUE,
+      method = "KR"
+    )
+  })
 
-  expect_warning(a1a <- eta_squared(m1, include_intercept = TRUE), regexp = "Intercept")
-  expect_warning(a1b <- eta_squared(m1, include_intercept = FALSE), regexp = NA)
+  expect_warning(
+    {
+      a1a <- eta_squared(m1, include_intercept = TRUE)
+    },
+    regexp = "Intercept"
+  )
+  expect_warning(
+    {
+      a1b <- eta_squared(m1, include_intercept = FALSE)
+    },
+    regexp = NA
+  )
   expect_equal(a1a, a1b)
   expect_equal(nrow(a1a), 1L)
 
-  expect_warning(a2a <- eta_squared(m2, include_intercept = TRUE), regexp = NA)
-  expect_warning(a2b <- eta_squared(m2, include_intercept = FALSE), regexp = NA)
+  expect_warning(
+    {
+      a2a <- eta_squared(m2, include_intercept = TRUE)
+    },
+    regexp = NA
+  )
+  expect_warning(
+    {
+      a2b <- eta_squared(m2, include_intercept = FALSE)
+    },
+    regexp = NA
+  )
   expect_equal(nrow(a2a), 2L)
   expect_equal(nrow(a2b), 1L)
-  expect_equal(a1a, a2a[2, ], ignore_attr = TRUE)
+  expect_equal(a1a, a2a[2L, ], ignore_attr = TRUE)
 })
 
 
@@ -546,17 +574,18 @@ test_that("car MVM", {
     id = 1:8
   )
 
-  ds_long <-
-    datawizard::reshape_longer(ds,
-      select = 1:4,
-      names_to = "ind_var",
-      values_to = "score"
-    )
+  ds_long <- datawizard::reshape_longer(ds,
+    select = 1:4,
+    names_to = "ind_var",
+    values_to = "score"
+  )
 
 
   fit <- lm(cbind(I, II, III, IV) ~ 1, data = ds)
-  in_rep <- data.frame(ind_var = gl(4, 1))
-  suppressMessages(A_car <- car::Anova(fit, idata = in_rep, idesign = ~ind_var))
+  in_rep <- data.frame(ind_var = gl(4L, 1L))
+  suppressMessages({
+    A_car <- car::Anova(fit, idata = in_rep, idesign = ~ind_var)
+  })
 
   eta_car <- effectsize::eta_squared(A_car, ci = NULL)[[2]]
 
@@ -570,11 +599,13 @@ test_that("car MVM", {
   # Complex ---
   data(obk.long, package = "afex")
 
-  suppressMessages(mod <- afex::aov_ez("id", "value", obk.long,
-    between = c("treatment", "gender"),
-    within = c("phase", "hour"),
-    observed = "gender"
-  ))
+  suppressMessages({
+    mod <- afex::aov_ez("id", "value", obk.long,
+      between = c("treatment", "gender"),
+      within = c("phase", "hour"),
+      observed = "gender"
+    )
+  })
   expect_equal(
     sort(eta_squared(mod$Anova, generalized = "gender")[[2]]),
     sort(mod$anova_table$ges)
@@ -592,7 +623,7 @@ test_that("Anova.mlm Manova", {
 
   mod <- lm(cbind(mpg, qsec, disp) ~ am_f * cyl_f, data = mtcars)
 
-  Manova <- car::Manova(mod, type = 2)
+  Manova <- car::Manova(mod, type = 2L)
 
   expect_true(is.null(summary(Manova, univariate = TRUE)[["univariate.tests"]]))
   expect_error(eta_squared(Manova), regexp = NA)
@@ -622,8 +653,8 @@ test_that("merMod and lmerModLmerTest", {
 
   data("sleepstudy", package = "lme4")
 
-  m <- lme4::lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
-  mtest <- lmerTest::lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
+  m <- lme4::lmer(Reaction ~ Days + (Days | Subject), data = sleepstudy)
+  mtest <- lmerTest::lmer(Reaction ~ Days + (Days | Subject), data = sleepstudy)
 
   expect_equal(
     eta_squared(m),
@@ -676,7 +707,7 @@ test_that("ets_squared | rms", {
 
   skip_if_not_installed("car")
   skip_if_not_installed("base", minimum_version = "3.6.1")
-  b_lm <- car::Anova(lm(mpg ~ cyl + am, data = mtcars), type = 2)
+  b_lm <- car::Anova(lm(mpg ~ cyl + am, data = mtcars), type = 2L)
   out_lm <- eta_squared(b_lm)
   expect_equal(out[1:2, ], out_lm, ignore_attr = TRUE)
 })