fix CRAN unicode issue (#521)

easystats · Oct 18, 2022 · fb7137d · fb7137d
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: effectsize
 Title: Indices of Effect Size
-Version: 0.8.0.0001
+Version: 0.8.1
 Authors@R: 
     c(person(given = "Mattan S.",
              family = "Ben-Shachar",

diff --git a/NEWS.md b/NEWS.md
@@ -1,4 +1,4 @@
-# effectsize 0.8.0.0001
+# effectsize 0.8.1
 
 ## Changes
 

diff --git a/R/is_effectsize_name.R b/R/is_effectsize_name.R
@@ -42,99 +42,12 @@ get_effectsize_label <- function(x, ignore_case = TRUE, use_symbols = getOption(
 
 # es_info -----------------------------------------------------------------
 
-
-#' List of effect size names
-#'
-#' Can always add more info here if need be...
-#'
-#' @keywords internal
-es_info <- matrix(
-  c(
-    ## Diffs
-    "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,
-    "Mahalanobis_D", "Mahalanobis' D", NA, "onetail", 0, Inf, 0,
-
-    ## xtab cor
-    "Cramers_v", "Cramer's V", NA, "onetail", 0, 1, 0,
-    "Cramers_v_adjusted", "Cramer's V (adj.)", NA, "onetail", 0, 1, 0,
-    "Tschuprows_t", "Tschuprow's T", NA, "onetail", 0, 1, 0,
-    "phi", "Phi", "\u03D5", "onetail", 0, 1, 0,
-    "phi_adjusted", "Phi (adj.)", "\u03D5 (adj.)", "onetail", 0, 1, 0,
-    "Pearsons_c", "Pearson's C", NA, "onetail", 0, 1, 0,
-    "Cohens_w", "Cohen's w", NA, "onetail", 0, Inf, 0,
-    "Fei", "Fei", "\u05E4\u200E", "onetail", 0, 1, 0,
-
-    ## xtab 2x2
-    "Cohens_h", "Cohen's h", NA, "twotail", -pi, pi, 0,
-    "Odds_ratio", "Odds ratio", NA, "twotail", 0, Inf, 1,
-    "log_Odds_ratio", "log(Odds ratio)", NA, "twotail", -Inf, Inf, 0,
-    "Risk_ratio", "Risk ratio", NA, "twotail", 0, Inf, 1,
-    "log_Risk_ratio", "log(Risk ratio)", NA, "twotail", -Inf, Inf, 0,
-
-    ## xtab dep
-    "Cohens_g", "Cohen's g", NA, "onetail", -0.5, 0.5, 0,
-
-    ## ANOVA
-    "Eta2", "Eta2", "\u03B7\u00b2", "onetail", 0, 1, 0,
-    "Eta2_partial", "Eta2 (partial)", "\u03B7\u00b2 (partial)", "onetail", 0, 1, 0,
-    "Eta2_generalized", "Eta2 (generalized)", "\u03B7\u00b2 (generalized)", "onetail", 0, 1, 0,
-    "Epsilon2", "Epsilon2", "\u03B5\u00b2", "onetail", 0, 1, 0,
-    "Epsilon2_partial", "Epsilon2 (partial)", "\u03B5\u00b2 (partial)", "onetail", 0, 1, 0,
-    "Omega2", "Omega2", "\u03C9\u00b2", "onetail", 0, 1, 0,
-    "Omega2_partial", "Omega2 (partial)", "\u03C9\u00b2 (partial)", "onetail", 0, 1, 0,
-    "Cohens_f", "Cohen's f", NA, "onetail", 0, Inf, 0,
-    "Cohens_f_partial", "Cohen's f (partial)", NA, "onetail", 0, Inf, 0,
-    "Cohens_f2", "Cohen's f2", "Cohen's f\u00b2", "onetail", 0, Inf, 0,
-    "Cohens_f2_partial", "Cohen's f2 (partial)", "Cohen's f\u00b2 (partial)", "onetail", 0, Inf, 0,
-
-    ## Rank
-    "r_rank_biserial", "r (rank biserial)", NA, "twotail", -1, 1, 0,
-    "Kendalls_W", "Kendall's W", NA, "onetail", 0, 1, 0,
-    "rank_epsilon_squared", "Epsilon2 (rank)", "\u03B5\u00b2(R)", "onetail", 0, 1, 0,
-    "rank_eta_squared", "Eta2 (rank)", "\u03B7\u00b2(H)", "onetail", 0, 1, 0,
-
-    ## CLES
-    "p_superiority", "Pr(superiority)", NA, "twotail", 0, 1, 0.5,
-    "WMW_odds", "WMW Odds", NA, "twotail", 0, Inf, 1,
-    "Cohens_U1", "Cohen's U1", NA, "onetail", 0, 1, 0,
-    "Cohens_U2", "Cohen's U2", NA, "onetail", 0.5, 1, 0.5,
-    "Cohens_U3", "Cohen's U3", NA, "twotail", 0, 1, 0.5,
-    "overlap", "Overlap", NA, "onetail", 0, 1, 1,
-
-    ## Other
-    "r", "r", NA, "twotail", -1, 1, 0,
-    "d", "d", NA, "twotail", -Inf, Inf, 0,
-
-    ## Std Coefficient
-    "Std_Coefficient", "Coefficient (std.)", NA, "twotail", -Inf, Inf, 0,
-    "Std_Odds_ratio", "Odds Ratio (std.)", NA, "twotail", 0, Inf, 1,
-    "Std_Risk_ratio", "Risk Ratio (std.)", NA, "twotail", 0, Inf, 1,
-    "Std_IRR", "IRR (std.)", "twotail", NA, 0, Inf, 1,
-    "Std_Median", "Median (std.)", NA, "twotail", -Inf, Inf, 0,
-    "Std_Mean", "Mean (std.)", NA, "twotail", -Inf, Inf, 0,
-    "Std_MAP", "MAP (std.)", NA, "twotail", -Inf, Inf, 0
-  ),
-  ncol = 7, byrow = TRUE,
-  dimnames = list(NULL, c("name", "label", "symbol", "direction", "lb", "ub", "null"))
-)
-es_info <- as.data.frame(es_info, stringsAsFactors = FALSE)
-es_info$lb <- as.numeric(es_info$lb)
-es_info$ub <- as.numeric(es_info$ub)
-es_info$null <- as.numeric(es_info$null)
-es_info$symbol[is.na(es_info$symbol)] <- es_info$label[is.na(es_info$symbol)]
-rownames(es_info) <- es_info$name
-
+# See data-raw/es_info.R
 
 # Utils -------------------------------------------------------------------
 
 
 #' @keywords internal
 .resolve_use_symbols <- function(use_symbols) {
-  use_symbols &&
-    !(
-      (Sys.info()["sysname"] == "windows" || grepl("^mingw", R.version$os)) &&
-        getRversion() < "4.2"
-    )
+  use_symbols && l10n_info()[["UTF-8"]]
 }
diff --git a/R/sysdata.rda b/R/sysdata.rda
diff --git a/WIP/convert_stat_H.R b/WIP/convert_stat_H.R
@@ -0,0 +1,18 @@
+#' Convert H statistic to Rank Epsilon / Eta Squared
+#'
+#' @param H Kruskal-Wallis rank sum test statistic. See [stats::kruskal.test()]
+#' @param N Total sample size
+#' @param k Number of groups
+#'
+#' @export
+h_to_epsilon <- function(H, N) {
+  H / ((N^2 - 1) / (N + 1))
+}
+
+#' @export
+#' @rdname h_to_epsilon
+h_to_epsilon <- function(H, N, k) {
+  (H - k + 1) / (N - k)
+}
+
+# TODO use these internally
diff --git a/data-raw/es_info.R b/data-raw/es_info.R
@@ -0,0 +1,73 @@
+es_info <- tibble::tribble(
+  ~name, ~label, ~symbol, ~direction, ~lb, ~ub, ~null,
+  ## Std. diffs
+  "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,
+  "Mahalanobis_D", "Mahalanobis' D", NA, "onetail", 0, Inf, 0,
+
+  ## xtab cor
+  "Cramers_v", "Cramer's V", NA, "onetail", 0, 1, 0,
+  "Cramers_v_adjusted", "Cramer's V (adj.)", NA, "onetail", 0, 1, 0,
+  "Tschuprows_t", "Tschuprow's T", NA, "onetail", 0, 1, 0,
+  "phi", "Phi", "\u03D5", "onetail", 0, 1, 0,
+  "phi_adjusted", "Phi (adj.)", "\u03D5 (adj.)", "onetail", 0, 1, 0,
+  "Pearsons_c", "Pearson's C", NA, "onetail", 0, 1, 0,
+  "Cohens_w", "Cohen's w", NA, "onetail", 0, Inf, 0,
+  "Fei", "Fei", "\u05E4\u200E", "onetail", 0, 1, 0,
+
+  ## xtab 2x2
+  "Cohens_h", "Cohen's h", NA, "twotail", -pi, pi, 0,
+  "Odds_ratio", "Odds ratio", NA, "twotail", 0, Inf, 1,
+  "log_Odds_ratio", "log(Odds ratio)", NA, "twotail", -Inf, Inf, 0,
+  "Risk_ratio", "Risk ratio", NA, "twotail", 0, Inf, 1,
+  "log_Risk_ratio", "log(Risk ratio)", NA, "twotail", -Inf, Inf, 0,
+
+  ## xtab dep
+  "Cohens_g", "Cohen's g", NA, "onetail", -0.5, 0.5, 0,
+
+  ## ANOVA
+  "Eta2", "Eta2", "\u03B7\u00b2", "onetail", 0, 1, 0,
+  "Eta2_partial", "Eta2 (partial)", "\u03B7\u00b2 (partial)", "onetail", 0, 1, 0,
+  "Eta2_generalized", "Eta2 (generalized)", "\u03B7\u00b2 (generalized)", "onetail", 0, 1, 0,
+  "Epsilon2", "Epsilon2", "\u03B5\u00b2", "onetail", 0, 1, 0,
+  "Epsilon2_partial", "Epsilon2 (partial)", "\u03B5\u00b2 (partial)", "onetail", 0, 1, 0,
+  "Omega2", "Omega2", "\u03C9\u00b2", "onetail", 0, 1, 0,
+  "Omega2_partial", "Omega2 (partial)", "\u03C9\u00b2 (partial)", "onetail", 0, 1, 0,
+  "Cohens_f", "Cohen's f", NA, "onetail", 0, Inf, 0,
+  "Cohens_f_partial", "Cohen's f (partial)", NA, "onetail", 0, Inf, 0,
+  "Cohens_f2", "Cohen's f2", "Cohen's f\u00b2", "onetail", 0, Inf, 0,
+  "Cohens_f2_partial", "Cohen's f2 (partial)", "Cohen's f\u00b2 (partial)", "onetail", 0, Inf, 0,
+
+  ## Rank
+  "r_rank_biserial", "r (rank biserial)", NA, "twotail", -1, 1, 0,
+  "Kendalls_W", "Kendall's W", NA, "onetail", 0, 1, 0,
+  "rank_epsilon_squared", "Epsilon2 (rank)", "\u03B5\u00b2(R)", "onetail", 0, 1, 0,
+  "rank_eta_squared", "Eta2 (rank)", "\u03B7\u00b2(H)", "onetail", 0, 1, 0,
+
+  ## CLES
+  "p_superiority", "Pr(superiority)", NA, "twotail", 0, 1, 0.5,
+  "WMW_odds", "WMW Odds", NA, "twotail", 0, Inf, 1,
+  "Cohens_U1", "Cohen's U1", NA, "onetail", 0, 1, 0,
+  "Cohens_U2", "Cohen's U2", NA, "onetail", 0.5, 1, 0.5,
+  "Cohens_U3", "Cohen's U3", NA, "twotail", 0, 1, 0.5,
+  "overlap", "Overlap", NA, "onetail", 0, 1, 1,
+
+  ## Other
+  "r", "r", NA, "twotail", -1, 1, 0,
+  "d", "d", NA, "twotail", -Inf, Inf, 0,
+
+  ## Std Coefficient
+  "Std_Coefficient", "Coefficient (std.)", NA, "twotail", -Inf, Inf, 0,
+  "Std_Odds_ratio", "Odds Ratio (std.)", NA, "twotail", 0, Inf, 1,
+  "Std_Risk_ratio", "Risk Ratio (std.)", NA, "twotail", 0, Inf, 1,
+  "Std_IRR", "IRR (std.)", "twotail", NA, 0, Inf, 1,
+  "Std_Median", "Median (std.)", NA, "twotail", -Inf, Inf, 0,
+  "Std_Mean", "Mean (std.)", NA, "twotail", -Inf, Inf, 0,
+  "Std_MAP", "MAP (std.)", NA, "twotail", -Inf, Inf, 0
+)
+
+es_info <- as.data.frame(es_info)
+es_info[is.na(es_info[["symbol"]]), "symbol"] <- es_info[is.na(es_info[["symbol"]]), "label"]
+rownames(es_info) <- es_info[["name"]]
+usethis::use_data(es_info, internal = TRUE)
diff --git a/dev/rhub.R b/dev/rhub.R
@@ -0,0 +1,5 @@
+library(rhub)
+
+# validate_email()
+# list_validated_emails()
+check(platforms = "debian-clang-devel")
diff --git a/man/es_info.Rd b/man/es_info.Rd
diff --git a/tests/testthat/test-eta_squared.R b/tests/testthat/test-eta_squared.R
@@ -494,7 +494,10 @@ test_that("afex | mixed()", {
 
   data(md_15.1, package = "afex")
   # random intercept plus random slope
-  t15.4a <- afex::mixed(iq ~ timecat + (1 + time | id), data = md_15.1)
+  t15.4a <- afex::mixed(iq ~ timecat + (1 + time | id),
+    data = md_15.1,
+    method = "S"
+  )
   expect_equal(
     eta_squared(t15.4a),
     eta_squared(t15.4a$full_model)

diff --git a/tests/testthat/test-print.R b/tests/testthat/test-print.R
@@ -1,3 +1,4 @@
+# library(testthat)
 
 test_that("print | effectsize table", {
   ## digits
@@ -168,9 +169,7 @@ test_that("rules", {
 
 
 test_that("printing symbols works as expected", {
-  skip_if(getRversion() < 4.2 &&
-    (Sys.info()["sysname"] == "windows" ||
-      grepl("^mingw", R.version$os)))
+  skip_if_not(l10n_info()[["UTF-8"]])
 
   RCT <- matrix(c(71, 50, 30, 100), nrow = 2L)
   P <- phi(RCT)

diff --git a/vignettes/anovaES.Rmd b/vignettes/anovaES.Rmd
@@ -233,7 +233,12 @@ always the case.
 
 For example, in linear mixed models (LMM/HLM/MLM), the estimation of all required *SS*s is not straightforward. However, we can still *approximate* these effect sizes (only their partial versions) based on the **test-statistic approximation method** (learn more in the [*Effect Size from Test Statistics* vignette](https://easystats.github.io/effectsize/articles/from_test_statistics.html)).
 
-```{r, eval=require(lmerTest)}
+```{r, echo = FALSE, eval=TRUE}
+lmm_pkgs <- c("lmerTest", "lme4")
+eval_lmm <- all(sapply(lmm_pkgs, requireNamespace, quietly = TRUE))
+```
+
+```{r, eval=eval_lmm}
 library(lmerTest)
 
 fit_lmm <- lmer(Reaction ~ Days + (Days | Subject), sleepstudy)
@@ -246,7 +251,7 @@ F_to_eta2(45.8, df = 1, df_error = 17)
 Or directly with `eta_squared() and co.:
 
 
-```{r, eval=require(lmerTest)}
+```{r, eval=eval_lmm}
 eta_squared(fit_lmm)
 epsilon_squared(fit_lmm)
 omega_squared(fit_lmm)