{"id":16707,"date":"2020-06-01T21:46:14","date_gmt":"2020-06-01T20:46:14","guid":{"rendered":"https:\/\/www.datanovia.com\/en\/?p=16707"},"modified":"2020-06-03T07:55:54","modified_gmt":"2020-06-03T06:55:54","slug":"comment-ajouter-des-p-values-sur-des-ggplots-basiques","status":"publish","type":"post","link":"https:\/\/www.datanovia.com\/en\/fr\/blog\/comment-ajouter-des-p-values-sur-des-ggplots-basiques\/","title":{"rendered":"Comment Ajouter des P-Values sur des GGPLOTS Basiques"},"content":{"rendered":"<div id=\"rdoc\">\n<p>Cet article d\u00e9crit les bases pour calculer et <strong>ajouter des p-values aux graphiques ggplots basiques<\/strong> en utilisant les packages R <em>rstatix<\/em> et <em>ggpubr<\/em>.<\/p>\n<p>Vous apprendrez \u00e0:<\/p>\n<ul>\n<li>Effectuer des comparaisons de moyennes par paires et ajouter les p-values sur des box plots et bar plots baiques.<\/li>\n<li>Afficher les p-values ajust\u00e9es et les niveaux de significativit\u00e9 sur les graphiques<\/li>\n<li>Formater les \u00e9tiquettes de p-values<\/li>\n<li>Sp\u00e9cifier manuellement la position y des \u00e9tiquettes de p-values et raccourcir la largeur des crochets<\/li>\n<\/ul>\n<p>Nous suivrons les \u00e9tapes suivantes pour ajouter des niveaux de significativit\u00e9 sur un ggplot:<\/p>\n<div class=\"block\">\n<ol style=\"list-style-type: decimal;\">\n<li>Calculer facilement des tests statistiques (<code>t_test()<\/code> ou <code>wilcox_test()<\/code>) en utilisant le package <code>rstatix<\/code><\/li>\n<li>Auto-calculez les positions des \u00e9tiquettes des p-values en utilisant la fonction <code>add_xy_position()<\/code> [dans le package rstatix].<\/li>\n<li>Ajoutez les p-values au graphique en utilisant la fonction <code>stat_pvalue_manual()<\/code> [dans le package ggpubr]. Les options cl\u00e9s suivantes sont illustr\u00e9es dans certains des exemples:\n<ul>\n<li>L\u2019option <code>bracket.nudge.y<\/code> est utilis\u00e9e pour monter ou descendre les crochets.<\/li>\n<li>L\u2019option <code>step.increase<\/code> est utilis\u00e9e pour ajouter de l\u2019espace entre les crochets.<\/li>\n<li>L\u2019option <code>vjust<\/code> est utilis\u00e9e pour ajuster verticalement la position des \u00e9tiquettes des p-values<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<\/div>\n<p>Notez que, dans certains cas, les \u00e9tiquettes de p-values sont partiellement cach\u00e9es par la bordure sup\u00e9rieure du graphique. Dans ce cas, la fonction ggplot2 <code>scale_y_continuous(expand = expansion(mult = c(0, 0.1)))<\/code> peut \u00eatre utilis\u00e9e pour <a href=\"https:\/\/www.datanovia.com\/en\/fr\/blog\/ggplot-facet-comment-ajouter-de-lespace-entre-les-etiquettes-en-haut-du-graphique-et-la-bordure-du-plot\/\">ajouter des espaces entre les \u00e9tiquettes et la bordure sup\u00e9rieure du graphique<\/a>. L\u2019option <code>mult = c(0, 0.1)<\/code> indique que des espaces de 0% et 10% sont respectivement ajout\u00e9s en bas et en haut du graphique.<\/p>\n<p>Sommaire:<\/p>\n<div id=\"TOC\">\n<ul>\n<li><a href=\"#pr\u00e9requis\">Pr\u00e9requis<\/a><\/li>\n<li><a href=\"#pr\u00e9paration-des-donn\u00e9es\">Pr\u00e9paration des donn\u00e9es<\/a><\/li>\n<li><a href=\"#comparer-deux-moyens\">Comparer deux moyens<\/a>\n<ul>\n<li><a href=\"#comparer-deux-groupes-ind\u00e9pendants\">Comparer deux groupes ind\u00e9pendants<\/a><\/li>\n<li><a href=\"#comparer-des-\u00e9chantillons-appari\u00e9s\">Comparer des \u00e9chantillons appari\u00e9s<\/a><\/li>\n<\/ul>\n<\/li>\n<li><a href=\"#comparaisons-par-paires\">Comparaisons par paires<\/a>\n<ul>\n<li><a href=\"#cr\u00e9er-des-graphiques-simples\">Cr\u00e9er des graphiques simples<\/a><\/li>\n<li><a href=\"#test-statistique\">Test statistique<\/a><\/li>\n<li><a href=\"#cr\u00e9er-des-graphiques-avec-les-niveaux-de-significativit\u00e9\">Cr\u00e9er des graphiques avec les niveaux de significativit\u00e9<\/a><\/li>\n<li><a href=\"#comparaisons-par-rapport-\u00e0-un-groupe-de-r\u00e9f\u00e9rence\">Comparaisons par rapport \u00e0 un groupe de r\u00e9f\u00e9rence<\/a><\/li>\n<li><a href=\"#comparaisons-par-rapport-\u00e0-lensemble-basemean\">Comparaisons par rapport \u00e0 l\u2019ensemble (basemean)<\/a><\/li>\n<li><a href=\"#comparaisons-par-rapport-\u00e0-une-valeur-th\u00e9orique-test-\u00e0-un-\u00e9chantillon\">Comparaisons par rapport \u00e0 une valeur th\u00e9orique: test \u00e0 un \u00e9chantillon<\/a><\/li>\n<\/ul>\n<\/li>\n<li><a href=\"#conclusion\">Conclusion<\/a><\/li>\n<\/ul>\n<\/div>\n<div id=\"pr\u00e9requis\" class=\"section level2\">\n<h2>Pr\u00e9requis<\/h2>\n<p>Assurez-vous d\u2019avoir install\u00e9 les paquets R suivants:<\/p>\n<ul>\n<li><code>ggpubr<\/code> pour cr\u00e9er facilement des graphiques pr\u00eats \u00e0 la publication<\/li>\n<li><code>rstatix<\/code> contient des fonctions R facilitant les analyses statistiques.<\/li>\n<\/ul>\n<p>Commencez par charger les packages requis suivants:<\/p>\n<pre class=\"r\"><code>library(ggpubr)\r\nlibrary(rstatix)<\/code><\/pre>\n<\/div>\n<div id=\"pr\u00e9paration-des-donn\u00e9es\" class=\"section level2\">\n<h2>Pr\u00e9paration des donn\u00e9es<\/h2>\n<pre class=\"r\"><code># Transformer `dose` en variable factorielle\r\ndf &lt;- ToothGrowth\r\ndf$dose &lt;- as.factor(df$dose)\r\nhead(df, 3)<\/code><\/pre>\n<pre><code>##    len supp dose\r\n## 1  4.2   VC  0.5\r\n## 2 11.5   VC  0.5\r\n## 3  7.3   VC  0.5<\/code><\/pre>\n<\/div>\n<div id=\"comparer-deux-moyens\" class=\"section level2\">\n<h2>Comparer deux moyens<\/h2>\n<p>Pour comparer les moyennes de deux groupes, vous pouvez utiliser soit la fonction <code>t_test()<\/code> (param\u00e9trique) ou <code>wilcox_test()<\/code> (non-param\u00e9trique). Dans l\u2019exemple suivant, le test t sera illustr\u00e9.<\/p>\n<div id=\"comparer-deux-groupes-ind\u00e9pendants\" class=\"section level3\">\n<h3>Comparer deux groupes ind\u00e9pendants<\/h3>\n<div id=\"box-plot-avec-p-values\" class=\"section level4\">\n<h4>Box plot avec p-values<\/h4>\n<pre class=\"r\"><code># Test statistique\r\nstat.test &lt;- df %&gt;%\r\n  t_test(len ~ supp) %&gt;%\r\n  add_significance()\r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 1 x 9\r\n##   .y.   group1 group2    n1    n2 statistic    df      p p.signif\r\n## * &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;  &lt;int&gt; &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;  &lt;dbl&gt; &lt;chr&gt;   \r\n## 1 len   OJ     VC        30    30      1.92  55.3 0.0606 ns<\/code><\/pre>\n<pre class=\"r\"><code># Box plot avec p-values\r\nbxp &lt;- ggboxplot(df, x = \"supp\", y = \"len\", fill = \"#00AFBB\")\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"supp\")\r\nbxp + \r\n  stat_pvalue_manual(stat.test, label = \"p\") +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.1)))\r\n\r\n# Personnaliser les \u00e9tiquettes de p-values en utilisant le format `glue` \r\n# https:\/\/github.com\/tidyverse\/glue\r\nbxp + stat_pvalue_manual(\r\n  stat.test, label = \"T-test, p = {p}\",\r\n  vjust = -1, bracket.nudge.y = 1\r\n  ) +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-compare-means-two-independent-groups-box-plot-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-compare-means-two-independent-groups-box-plot-2.png\" width=\"288\" \/><\/p>\n<\/div>\n<div id=\"donn\u00e9es-group\u00e9es\" class=\"section level4\">\n<h4>Donn\u00e9es group\u00e9es<\/h4>\n<p>Regroupez les donn\u00e9es en fonction de la variable <code>dose<\/code> et comparez ensuite les niveaux de la variable <code>supp<\/code>.<\/p>\n<pre class=\"r\"><code># Test statistique\r\nstat.test &lt;- df %&gt;%\r\n  group_by(dose) %&gt;%\r\n  t_test(len ~ supp) %&gt;%\r\n  adjust_pvalue() %&gt;%\r\n  add_significance(\"p.adj\")\r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 3 x 11\r\n##   dose  .y.   group1 group2    n1    n2 statistic    df       p   p.adj p.adj.signif\r\n## * &lt;fct&gt; &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;  &lt;int&gt; &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;   &lt;dbl&gt;   &lt;dbl&gt; &lt;chr&gt;       \r\n## 1 0.5   len   OJ     VC        10    10    3.17    15.0 0.00636 0.0127  *           \r\n## 2 1     len   OJ     VC        10    10    4.03    15.4 0.00104 0.00312 **          \r\n## 3 2     len   OJ     VC        10    10   -0.0461  14.0 0.964   0.964   ns<\/code><\/pre>\n<pre class=\"r\"><code># Box plot avec p-values\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"supp\")\r\nbxp &lt;- ggboxplot(df, x = \"supp\", y = \"len\", fill = \"#00AFBB\",\r\n                 facet.by = \"dose\")\r\nbxp + \r\n  stat_pvalue_manual(stat.test, label = \"p.adj\") +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.10)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-grouped-data-compare-two-independent-groups-1.png\" width=\"528\" \/><\/p>\n<\/div>\n<div id=\"afficher-les-p-values-si-elles-sont-significatives-sinon-afficher-ns\" class=\"section level4\">\n<h4>Afficher les p-values si elles sont significatives sinon afficher ns<\/h4>\n<p>Cette section d\u00e9crit comment afficher les p-values lorsqu\u2019elles sont significatives et montrer \u201cns\u201d lorsque les p-values ne sont pas significatives.<\/p>\n<pre class=\"r\"><code># Ajouter une colonne d'\u00e9tiquettes personnalis\u00e9es\r\n# indiquer les p-values ajust\u00e9es si elles sont significatives, sinon \"ns\" \r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"supp\")\r\nstat.test$custom.label &lt;- ifelse(stat.test$p.adj &lt;= 0.05, stat.test$p.adj, \"ns\")\r\n\r\n# Visualisation\r\nbxp + \r\n  stat_pvalue_manual(stat.test, label = \"custom.label\") +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.10)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-show-significant-p-values-otherwise-ns-1.png\" width=\"528\" \/><\/p>\n<\/div>\n<div id=\"formater-les-p-values-en-utilisant-loption-de-pr\u00e9cision-ou-accuracy\" class=\"section level4\">\n<h4>Formater les p-values en utilisant l\u2019option de pr\u00e9cision ou accuracy<\/h4>\n<p>Les p-values seront format\u00e9es en utilisant \u201c&lt;\u201d et \u201c&gt;\u201d.<\/p>\n<pre class=\"r\"><code>stat.test &lt;- stat.test %&gt;% add_xy_position(x = \"supp\")\r\nstat.test$p.format &lt;- p_format(\r\n  stat.test$p.adj, accuracy = 0.01,\r\n  leading.zero = FALSE\r\n  )\r\n# Visualisation\r\nbxp + \r\n  stat_pvalue_manual(stat.test, label = \"p.format\") +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.10)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-format-p-values-using-the-accuracy-option-1.png\" width=\"528\" \/><\/p>\n<\/div>\n<div id=\"formater-les-p-values-en-notation-scientifique\" class=\"section level4\">\n<h4>Formater les p-values en notation scientifique<\/h4>\n<pre class=\"r\"><code># Convertir les p-values en format scientifique\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"supp\")\r\nstat.test$p.scient &lt;- format(stat.test$p.adj, scientific = TRUE)\r\nbxp + \r\n  stat_pvalue_manual(stat.test, label = \"p.scient\") +\r\n   scale_y_continuous(expand = expansion(mult = c(0.05, 0.15)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-p-values-in-scientific-format-1.png\" width=\"528\" \/><\/p>\n<\/div>\n<\/div>\n<div id=\"comparer-des-\u00e9chantillons-appari\u00e9s\" class=\"section level3\">\n<h3>Comparer des \u00e9chantillons appari\u00e9s<\/h3>\n<pre class=\"r\"><code># Test statistique\r\nstat.test &lt;- df %&gt;%\r\n  t_test(len ~ supp, paired = TRUE) %&gt;%\r\n  add_significance()\r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 1 x 9\r\n##   .y.   group1 group2    n1    n2 statistic    df       p p.signif\r\n## * &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;  &lt;int&gt; &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;   &lt;dbl&gt; &lt;chr&gt;   \r\n## 1 len   OJ     VC        30    30      3.30    29 0.00255 **<\/code><\/pre>\n<pre class=\"r\"><code># Box plot avec p-values\r\nbxp &lt;-  ggpaired(df, x = \"supp\", y = \"len\", fill = \"#E7B800\",\r\n                 line.color = \"gray\", line.size = 0.4)\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"supp\")\r\nbxp + stat_pvalue_manual(stat.test, label = \"p.signif\")\r\n\r\n# Indiquer la p-value combin\u00e9e avec le niveau de significativit\u00e9\r\nbxp + \r\n  stat_pvalue_manual(stat.test, label = \"{p}{p.signif}\") +\r\n  scale_y_continuous(expand = expansion(mult = c(0.05, 0.10)))<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-compare-means-paired-groups-box-plot-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-compare-means-paired-groups-box-plot-2.png\" width=\"288\" \/><\/p>\n<\/div>\n<\/div>\n<div id=\"comparaisons-par-paires\" class=\"section level2\">\n<h2>Comparaisons par paires<\/h2>\n<div id=\"cr\u00e9er-des-graphiques-simples\" class=\"section level3\">\n<h3>Cr\u00e9er des graphiques simples<\/h3>\n<pre class=\"r\"><code># Box plots\r\nbxp &lt;- ggboxplot(df, x = \"dose\", y = \"len\", fill = \"dose\", \r\n                 palette = c(\"#00AFBB\", \"#E7B800\", \"#FC4E07\"))\r\nbxp\r\n# Bar plots repr\u00e9sentant la moyenne +\/- l'\u00e9cart-type\r\nbp &lt;- ggbarplot(df, x = \"dose\", y = \"len\", add = \"mean_sd\", fill = \"dose\", \r\n                palette = c(\"#00AFBB\", \"#E7B800\", \"#FC4E07\"))\r\nbp<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-create-simple-plots-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-create-simple-plots-2.png\" width=\"288\" \/><\/p>\n<\/div>\n<div id=\"test-statistique\" class=\"section level3\">\n<h3>Test statistique<\/h3>\n<p>Dans l\u2019exemple suivant, nous allons effectuer un test-T en utilisant la fonction <code>t_test()<\/code> [package rstatix]. Il est \u00e9galement possible d\u2019utiliser la fonction <code>wilcox_test()<\/code>.<\/p>\n<pre class=\"r\"><code>stat.test &lt;- df %&gt;% t_test(len ~ dose)\r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 3 x 10\r\n##   .y.   group1 group2    n1    n2 statistic    df        p    p.adj p.adj.signif\r\n## * &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;  &lt;int&gt; &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;    &lt;dbl&gt;    &lt;dbl&gt; &lt;chr&gt;       \r\n## 1 len   0.5    1         20    20     -6.48  38.0 1.27e- 7 2.54e- 7 ****        \r\n## 2 len   0.5    2         20    20    -11.8   36.9 4.40e-14 1.32e-13 ****        \r\n## 3 len   1      2         20    20     -4.90  37.1 1.91e- 5 1.91e- 5 ****<\/code><\/pre>\n<\/div>\n<div id=\"cr\u00e9er-des-graphiques-avec-les-niveaux-de-significativit\u00e9\" class=\"section level3\">\n<h3>Cr\u00e9er des graphiques avec les niveaux de significativit\u00e9<\/h3>\n<pre class=\"r\"><code># Box plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"dose\")\r\nbxp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\", tip.length = 0.01)\r\n\r\n# Bar plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(fun = \"mean_sd\", x = \"dose\")\r\nbp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\", tip.length = 0.01)<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-simple-pairwise-comparisons-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-simple-pairwise-comparisons-2.png\" width=\"288\" \/><\/p>\n<p>Sp\u00e9cifier manuellement la position y des \u00e9tiquettes de p-values et raccourcir la largeur des crochets:<\/p>\n<pre class=\"r\"><code>bxp + \r\n  stat_pvalue_manual(\r\n    stat.test, label = \"p.adj.signif\", tip.length = 0.01,\r\n    y.position = c(35, 40, 35), bracket.shorten = 0.05\r\n    )<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-manual-p-value-label-y-position-1.png\" width=\"288\" \/><\/p>\n<\/div>\n<div id=\"comparaisons-par-rapport-\u00e0-un-groupe-de-r\u00e9f\u00e9rence\" class=\"section level3\">\n<h3>Comparaisons par rapport \u00e0 un groupe de r\u00e9f\u00e9rence<\/h3>\n<pre class=\"r\"><code># Tests statistiques\r\nstat.test &lt;- df %&gt;% t_test(len ~ dose, ref.group = \"0.5\") \r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 2 x 10\r\n##   .y.   group1 group2    n1    n2 statistic    df        p    p.adj p.adj.signif\r\n## * &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;  &lt;int&gt; &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;    &lt;dbl&gt;    &lt;dbl&gt; &lt;chr&gt;       \r\n## 1 len   0.5    1         20    20     -6.48  38.0 1.27e- 7 1.27e- 7 ****        \r\n## 2 len   0.5    2         20    20    -11.8   36.9 4.40e-14 8.80e-14 ****<\/code><\/pre>\n<pre class=\"r\"><code># Box plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"dose\")\r\nbxp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\", tip.length = 0.01)\r\n\r\n# Bar plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(fun = \"mean_sd\", x = \"dose\")\r\nbp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\", tip.length = 0.01)<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-comparisons-against-reference-groups-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-comparisons-against-reference-groups-2.png\" width=\"288\" \/><\/p>\n<\/div>\n<div id=\"comparaisons-par-rapport-\u00e0-lensemble-basemean\" class=\"section level3\">\n<h3>Comparaisons par rapport \u00e0 l\u2019ensemble (basemean)<\/h3>\n<p>Chaque groupe est compar\u00e9 \u00e0 tous les groupes combin\u00e9s.<\/p>\n<pre class=\"r\"><code># Tests statistiques\r\nstat.test &lt;- df %&gt;% t_test(len ~ dose, ref.group = \"all\") \r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 3 x 10\r\n##   .y.   group1 group2    n1    n2 statistic    df           p      p.adj p.adj.signif\r\n## * &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;  &lt;int&gt; &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;       &lt;dbl&gt;      &lt;dbl&gt; &lt;chr&gt;       \r\n## 1 len   all    0.5       60    20     5.82   56.4 0.000000290 0.00000087 ****        \r\n## 2 len   all    1         60    20    -0.660  57.5 0.512       0.512      ns          \r\n## 3 len   all    2         60    20    -5.61   66.5 0.000000425 0.00000087 ****<\/code><\/pre>\n<pre class=\"r\"><code># Box plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"dose\") \r\nbxp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\")\r\n\r\n# Pr\u00e9ciser manuellement la position y\r\nbxp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\", y.position = 35)\r\n\r\n# Bar plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(fun = \"mean_sd\", x = \"dose\")\r\nbp + stat_pvalue_manual(stat.test, label = \"p.adj.signif\")<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-comparisons-against-all-basemean-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-comparisons-against-all-basemean-2.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-comparisons-against-all-basemean-3.png\" width=\"288\" \/><\/p>\n<\/div>\n<div id=\"comparaisons-par-rapport-\u00e0-une-valeur-th\u00e9orique-test-\u00e0-un-\u00e9chantillon\" class=\"section level3\">\n<h3>Comparaisons par rapport \u00e0 une valeur th\u00e9orique: test \u00e0 un \u00e9chantillon<\/h3>\n<p>Le test \u00e0 un \u00e9chantillon est utilis\u00e9 pour comparer la moyenne d\u2019un \u00e9chantillon \u00e0 une moyenne standard (ou th\u00e9orique \/ hypoth\u00e9tique) connue (<code>mu<\/code>). La valeur par d\u00e9faut de `mu est z\u00e9ro.<\/p>\n<pre class=\"r\"><code># Tests statistiques\r\nstat.test &lt;- df %&gt;% \r\n  group_by(dose) %&gt;%\r\n  t_test(len ~ 1) %&gt;%\r\n  adjust_pvalue() %&gt;%\r\n  add_significance(\"p.adj\")\r\nstat.test<\/code><\/pre>\n<pre><code>## # A tibble: 3 x 10\r\n##   dose  .y.   group1 group2         n statistic    df        p    p.adj p.adj.signif\r\n## * &lt;fct&gt; &lt;chr&gt; &lt;chr&gt;  &lt;chr&gt;      &lt;int&gt;     &lt;dbl&gt; &lt;dbl&gt;    &lt;dbl&gt;    &lt;dbl&gt; &lt;chr&gt;       \r\n## 1 0.5   len   1      null model    20      10.5    19 2.24e- 9 2.24e- 9 ****        \r\n## 2 1     len   1      null model    20      20.0    19 3.22e-14 6.44e-14 ****        \r\n## 3 2     len   1      null model    20      30.9    19 1.03e-17 3.09e-17 ****<\/code><\/pre>\n<pre class=\"r\"><code># Box plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(x = \"dose\") \r\nbxp + stat_pvalue_manual(stat.test, x = \"dose\", label = \"p.adj.signif\")\r\n # bar plot\r\nstat.test &lt;- stat.test %&gt;% add_xy_position(fun = \"mean_sd\", x = \"dose\")\r\nbp + stat_pvalue_manual(stat.test, x = \"dose\", label = \"p.adj.signif\")<\/code><\/pre>\n<p><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-comparisons-against-null-1.png\" width=\"288\" \/><img decoding=\"async\" src=\"https:\/\/www.datanovia.com\/en\/wp-content\/uploads\/dn-tutorials\/ggpubr\/figures\/055-add-p-values-onto-basic-ggplots-comparisons-against-null-2.png\" width=\"288\" \/><\/p>\n<\/div>\n<\/div>\n<div id=\"conclusion\" class=\"section level2\">\n<h2>Conclusion<\/h2>\n<p>Cet article explique comment calculer et ajouter facilement des p-values sur des graphiques, tels que les box plots et les bar plots. Voir les autres questions fr\u00e9quemment pos\u00e9es : <a href=\"https:\/\/www.datanovia.com\/en\/fr\/blog\/tag\/ggpubr-fr\/\">ggpubr FAQ<\/a>.<\/p>\n<\/div>\n<\/div>\n<p><!--end rdoc--><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Cet article d\u00e9crit les bases pour calculer et ajouter des p-values aux graphiques ggplots basiques en utilisant les packages R rstatix et ggpubr. Vous apprendrez \u00e0: Effectuer des comparaisons de [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":16703,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"rating_form_position":"","rating_results_position":"","mr_structured_data_type":"","footnotes":""},"categories":[342],"tags":[350],"class_list":["post-16707","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-faq-fr","tag-ggpubr-fr"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Comment Ajouter des P-Values sur des GGPLOTS Basiques - Datanovia<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.datanovia.com\/en\/fr\/blog\/comment-ajouter-des-p-values-sur-des-ggplots-basiques\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Comment Ajouter des P-Values sur des GGPLOTS Basiques - Datanovia\" \/>\n<meta property=\"og:description\" content=\"Cet article d\u00e9crit les bases pour calculer et ajouter des p-values aux graphiques ggplots basiques en utilisant les packages R rstatix et ggpubr. 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