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ClustMC.Rproj

@@ -20,3 +20,5 @@ BuildType: Package
 PackageUseDevtools: Yes
 PackageInstallArgs: --no-multiarch --with-keep.source
 PackageRoxygenize: rd,collate,namespace
+
+SpellingDictionary: en_US

DESCRIPTION

@@ -3,7 +3,7 @@ Title: Cluster Based Multiple Comparisons
 Version: 0.0.0.9000
 Authors@R: 
  person("Santiago", "Garcia Sanchez", , "[email protected]", role = c("aut", "cre"))
-Description: Pruebas de comparaciones múltiples basadas en conglomerados.
+Description: Cluster-based multiple comparisons tests.
 License: MIT + file LICENSE
 Depends: 
  R (>= 2.10)

R/dgc.R

@@ -18,15 +18,16 @@ buscar_q <- function(valor_n, valor_k, valor_alfa = 0.05) {
  if (valor_n > 40) {
  valor_n <- 40
  } else if (valor_n < 2) {
- cli::cli_abort("Cada tratamiento debe tener al menos dos observaciones")
+ cli::cli_abort("Each treatment must have at least two observations.")
  }
 
  if (valor_k > 40) {
  valor_k <- 40
  } else if (valor_k < 3) {
  cli::cli_abort(paste(
- "Debe haber al menos tres tratamientos, se hallaron",
- valor_k
+ "There must be at least three treatments, but",
+ valor_k,
+ "were found."
  ))
  }
 
@@ -53,10 +54,10 @@ graficar_dendrograma_dgc <- function(dendrograma, c, abline_options, ...) {
  args <- list(...)
  plot_labels <- c("main", "sub", "xlab", "ylab")
  plot_args <- list(
- main = "Cluster Dendogram",
- sub = "Las diferencias por debajo de la linea no son significativas",
- xlab = "Grupos",
- ylab = "Distancia"
+ main = "Cluster dendrogram",
+ sub = "Differences below the line are not significant.",
+ xlab = "Groups",
+ ylab = "Distance"
  )
 
  for (label in plot_labels) {
@@ -76,54 +77,55 @@ graficar_dendrograma_dgc <- function(dendrograma, c, abline_options, ...) {
 
  # Alerta si la linea no es visible
  if (c > max(dendrograma$height)) {
- cli::cli_alert_info("Ninguna diferencia fue significativa, la linea podria no mostrarse")
+ cli::cli_alert_info("No differences were significant, the line may not be displayed.")
  } else if (c < min(dendrograma$height)) {
- cli::cli_alert_info("Todas las diferencias fueron significativas, la linea podria no mostrarse")
+ cli::cli_alert_info("All differences were significant, the line may not be displayed.")
  }
 }
 
-#' Test DGC
+#' DGC Test
 #'
-#' Prueba de Di Rienzo, Guzmán y Casanoves para comparaciones múltiples.
-#' Implementa un método basado en clusters para identificar grupos de medias no
-#' homogéneas.
+#' Di Rienzo, Guzman and Casanoves test for multiple comparisons.
+#' Implements a cluster-based method for identifying groups of nonhomogeneous
+#' means.
 #'
-#' @param y O bien un modelo (creado con `lm()` o `aov()`) o bien un vector
-#' numerico con los valores de la variable respuesta para cada unidad.
-#' @param trt Si `y` es un modelo, corresponde a la columna que indica los
-#' tratamientos. Si `y` es un vector, corresponde a un vector de la misma
-#' longitud que `y` con los tratamientos para cada unidad.
-#' @param alpha Valor equivalente a 0.05 o 0.01, correspondiente al nivel
-#' de significación del test. Por defecto toma el valor 0.05.
-#' @param show_plot Valor logico indicando si debe graficarse el dendrograma
-#' construido o no.
-#' @param console Valor logico indicando si deben imprimirse los resultados en
-#' consola o no.
-#' @param abline_options Lista con argumentos opcionales para la linea
-#' del dendograma.
-#' @param ... Argumentos opcionales para la funcion `plot()`.
+#' @param y Either a model (created with `lm()` o `aov()`) or a numerical vector
+#' with the values of the response variable for each unit.
+#' @param trt If `y` is a model, it corresponds to the column indicating the
+#' treatments. If `y` is a vector, it's a vector of the same length as `y`
+#' with the treatments for each unit.
+#' @param alpha Value equivalent to 0.05 or 0.01, corresponding to the
+#' significance level of the test. The default value is 0.05.
+#' @param show_plot Logical value indicating whether the constructed dendrogram
+#' should be plotted or not.
+#' @param console Logical value indicating whether the results should be printed
+#' on the console or not.
+#' @param abline_options List with optional arguments for the line in the
+#' dendrogram.
+#' @param ... Optional arguments for the `plot()` function.
 #'
-#' @returns Una lista con tres objetos `data.frame`:
-#' \item{estadisticas}{`data.frame` con estadisticas resumen segun tratamiento.}
-#' \item{grupos}{`data.frame` indicando el grupo al que es asignado cada
-#' tratamiento.}
-#' \item{parametros}{`data.frame` con los valores utilizados para el test.
-#' `tratamientos` es el numero total de tratamientos, `alpha` es el nivel de
-#' significación utilizado, `c` es el criterio de corte (indica la altura
-#' de la linea horizontal del dendrograma), `q` es el cuantil 1-alpha de la
-#' distribucion de Q (distancia del nodo raiz) bajo la hipotesis nula y
-#' `SEM` es una estimacion del error estandar de la media.}
+#' @returns A list with three `data.frame`:
+#' \item{stats}{`data.frame` containing summary statistics by treatment.}
+#' \item{groups}{data.frame indicating the group to which each treatment is
+#' assigned.}
+#' \item{parameters}{`data.frame` with the values used for the test.
+#' `treatments` is the total number of treatments, `alpha` is the
+#' significance level used, `c` is the cut-off criterion for the dendrogram
+#' (the height of the horizontal line of the dendrogram), `q` is the 1-alpha
+#' quantile of the distribution of Q (distance from the root node) under the
+#' null hypothesis and `SEM` SEM is an estimate of the standard error of the
+#' mean.}
 #' @export
 #'
 #' @examples
 #' data("PlantGrowth")
-#' # Utilizando vectores -------------------------------------------------------
-#' pesos <- PlantGrowth$weight
-#' tratamientos <- PlantGrowth$group
-#' dgc_test(y = pesos, trt = tratamientos, show_plot = FALSE)
-#' # Utilizando un modelo ------------------------------------------------------
-#' modelo <- lm(pesos ~ tratamientos)
-#' dgc_test(y = modelo, trt = "tratamientos", show_plot = FALSE)
+#' # Using vectors -------------------------------------------------------
+#' weights <- PlantGrowth$weight
+#' treatments <- PlantGrowth$group
+#' dgc_test(y = weights, trt = treatments, show_plot = FALSE)
+#' # Using a model ------------------------------------------------------
+#' model <- lm(weights ~ treatments)
+#' dgc_test(y = model, trt = "treatments", show_plot = FALSE)
 #' @references Di Rienzo, J.A., Guzmán, A.W., Casanoves, F. (2002): A multiple
 #' comparisons method based on the distribution of the root node distance of a
 #' binary tree. J. Agr.Biol. Environ. Stat. 7: 1-14.
@@ -139,8 +141,8 @@ dgc_test <- function(y, trt, alpha = 0.05, show_plot = T, console = T,
  # `trt` debe ser el nombre de una columna
  if (length(colnames(y$model)[which(colnames(y$model) == grupos)]) != 1) {
  cli::cli_abort(paste0(
- "No se encuentra la columna '", trt,
- "' en `y`"
+ "The column '", trt,
+ "' cannot be found in `y`"
  ))
  }
  }
@@ -178,8 +180,8 @@ dgc_test <- function(y, trt, alpha = 0.05, show_plot = T, console = T,
  # `alpha` debe tener un valor apropiado para calcular `Q`
  if (alpha != 0.05 & alpha != 0.01) {
  cli::cli_warn(
- paste0("`alpha` debe ser 0.05 o 0.01", ", no '", alpha, "'", ". Se utiliza
-  alpha = 0.05 por defecto.")
+ paste0("`alpha` must be either 0.05 o 0.01", ", not '", alpha, "'", ".
+ alpha = 0.05 will be used by default.")
  )
  alpha <- 0.05
  }
@@ -203,17 +205,17 @@ dgc_test <- function(y, trt, alpha = 0.05, show_plot = T, console = T,
  # Listas para return
  estadisticas <- as.data.frame(datos[order(datos$media), ])
  grupos <- procs::proc_sort(as.data.frame(stats::cutree(dendrograma, h = valor_c)))
- colnames(grupos) <- "grupo"
+ colnames(grupos) <- "group"
  parametros <- data.frame(
- "tratamientos" = k, "alpha" = alpha,
+ "treatments" = k, "alpha" = alpha,
  "c" = valor_c, "q" = valor_q, "SEM" = sqrt(MSE / n)
  )
 
  if (console) {
  print(grupos)
- cat("Los tratamientos de un mismo grupo no presentan diferencias significativas\n")
+ cat("Treatments within the same group are not significantly different\n")
  }
 
- output <- list("estadisticas" = estadisticas, "grupos" = grupos, "parametros" = parametros)
+ output <- list("stats" = estadisticas, "groups" = grupos, "parameters" = parametros)
  invisible(output)
 }

README.Rmd

@@ -43,7 +43,7 @@ El siguiente ejemplo aplica la Prueba de Di Rienzo, Guzmán y Casanoves para eva
 ```{r example}
 library(ClustMC)
 
-data("PlantGrowth")
+data(PlantGrowth)
 plants_weights <- PlantGrowth$weight
 plants_trt <- PlantGrowth$group
 

README.md

@@ -39,7 +39,7 @@ de tratamiento diferentes.
 ``` r
 library(ClustMC)
 
-data("PlantGrowth")
+data(PlantGrowth)
 plants_weights <- PlantGrowth$weight
 plants_trt <- PlantGrowth$group
 
@@ -50,8 +50,8 @@ dgc_test(y = anova_model, trt = "plants_trt")
 
 <img src="man/figures/README-example-1.png" width="100%" />
 
- #> grupo
+ #> group
  #> ctrl 1
  #> trt1 1
  #> trt2 2
- #> Los tratamientos de un mismo grupo no presentan diferencias significativas
+ #> Treatments within the same group are not significantly different

tests/testthat/test-dgc_test.R

@@ -14,27 +14,27 @@ test_that("se detecta alpha incorrecto", {
 test_that("se muestran corectamente las alertas", {
  expect_no_message(dgc_test(PlantGrowth$weight, PlantGrowth$group, alpha = 0.05))
  expect_message(dgc_test(PlantGrowth$weight, PlantGrowth$group, alpha = 0.01),
- regexp = "Ninguna diferencia fue significativa"
+ regexp = "No differences"
  )
  expect_message(dgc_test(iris$Sepal.Length, iris$Species),
- regexp = "Todas las diferencias"
+ regexp = "All differences"
  )
 })
 
 test_that("se muestra corectamente el error por columna inexistente", {
  modelo <- lm(data = PlantGrowth, weight ~ group)
  expect_no_error(dgc_test(modelo, "group"))
  expect_error(dgc_test(modelo, "columna_inexistente"),
- regexp = "No se encuentra la columna"
+ regexp = "The column.*cannot be found in"
  )
 })
 
 test_that("se muestran corectamente los errores por k y n", {
  expect_error(dgc_test(mtcars$mpg, mtcars$vs),
- regexp = "al menos.*tratamientos"
+ regexp = "at least.*treatments"
  )
  expect_error(dgc_test(mtcars$mpg, mtcars$wt),
- regexp = "al menos.*observaciones"
+ regexp = "at least.*observations"
  )
 })
 
@@ -62,25 +62,25 @@ test_that("se configuran correctamente los graficos", {
 })
 
 test_that("los returns son correctos", {
- expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$estadisticas,
+ expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$stats,
  type = "list"
  )
- expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$grupos,
+ expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$groups,
  type = "list"
  )
- expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$grupos[[1]],
+ expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$groups[[1]],
  type = "integer"
  )
- expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parametros,
+ expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parameters,
  type = "list"
  )
- expect_length(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parametros, n = 5)
- if (length(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parametros) == 5) {
- expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parametros[[1]],
+ expect_length(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parameters, n = 5)
+ if (length(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parameters) == 5) {
+ expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parameters[[1]],
  type = "integer"
  )
  for (i in 2:4) {
- expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parametros[2:5][[i]],
+ expect_type(dgc_test(PlantGrowth$weight, PlantGrowth$group)$parameters[2:5][[i]],
  type = "double"
  )
  }