From 09f5fe54ab24a2d2cda955db1249be850ee344ea Mon Sep 17 00:00:00 2001
From: Joseph Larmarange <joseph@larmarange.net>
Date: Fri, 27 Sep 2024 11:29:55 +0200
Subject: [PATCH] rebuild

---
 docs/analyses/contrastes.html                 |   2 +-
 docs/analyses/estimations-marginales.html     |  26 ++--
 docs/analyses/ggplot2.html                    |  18 +--
 docs/analyses/interactions.html               |  22 +--
 docs/analyses/likert.html                     |   2 +-
 docs/analyses/multicolinearite.html           |   4 +-
 docs/analyses/regression-lineaire.html        |   2 +-
 .../regression-logistique-binaire.html        |  14 +-
 docs/analyses/selection-modele-pas-a-pas.html | 132 +++++++++---------
 docs/analyses/statistique-bivariee.html       |  32 ++---
 docs/analyses/statistique-univariee.html      |  16 +--
 .../analyse-factorielle.html                  |  24 ++--
 docs/analyses_avancees/analyse-survie.html    |   2 +-
 ...lassification-ascendante-hierarchique.html |   2 +-
 docs/analyses_avancees/modeles-comptage.html  |   2 +-
 docs/analyses_avancees/modeles-incidence.html |   8 +-
 .../modeles-zero-inflated.html                |   2 +-
 .../regression-logistique-multinomiale.html   |   2 +-
 .../regression-logistique-ordinale.html       |   2 +-
 docs/bases/packages.html                      |   4 +-
 docs/bases/tableaux_donnees.html              |   2 +-
 .../graphiques-ponderes.html                  |   8 +-
 ...egression-logistique-binaire-ponderee.html |   6 +-
 docs/index.html                               |   2 +-
 docs/manipulation/couleurs.html               |   2 +-
 docs/manipulation/etiquettes-valeurs.html     |   2 +-
 docs/manipulation/etiquettes-variables.html   |   2 +-
 docs/manipulation/facteurs.html               |   2 +-
 docs/manipulation/import-export.html          |   2 +-
 docs/manipulation/pipe.html                   |   2 +-
 .../conditions-logiques.html                  |   2 +-
 docs/manipulation_avancee/tidyr.html          |   2 +-
 docs/search.json                              |   2 +-
 33 files changed, 177 insertions(+), 177 deletions(-)

diff --git a/docs/analyses/contrastes.html b/docs/analyses/contrastes.html
index 500f8e9..5a8b17f 100644
--- a/docs/analyses/contrastes.html
+++ b/docs/analyses/contrastes.html
@@ -6549,7 +6549,7 @@ <h1 class="title"><span id="sec-contrastes" class="quarto-section-identifier"><s
 </ul>
 </div>
   </div>
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+</footer><script>var lightboxQuarto = GLightbox({"descPosition":"bottom","selector":".lightbox","openEffect":"zoom","closeEffect":"zoom","loop":false});
 window.onload = () => {
   lightboxQuarto.on('slide_before_load', (data) => {
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diff --git a/docs/analyses/estimations-marginales.html b/docs/analyses/estimations-marginales.html
index eb068ea..6e9d4b9 100644
--- a/docs/analyses/estimations-marginales.html
+++ b/docs/analyses/estimations-marginales.html
@@ -1989,7 +1989,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-predictions-marginales-moyennes" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-predictions-marginales-moyennes-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1" data-glightbox="description: .lightbox-desc-1"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-1" data-gallery="quarto-lightbox-gallery-1"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-marginales-moyennes-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.1: Prédictions marginales moyennes
@@ -2003,7 +2003,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-predictions-marginales-moyennes-2" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
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+<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-2-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-2" data-gallery="quarto-lightbox-gallery-2"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-2-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-marginales-moyennes-2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.2: Prédictions marginales moyennes
@@ -2026,7 +2026,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-predictions-marginales-moyennes-3" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
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+<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-3-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-3" data-gallery="quarto-lightbox-gallery-3"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-moyennes-3-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-marginales-moyennes-3-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.3: Prédictions marginales moyennes
@@ -2733,7 +2733,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-predictions-marginales-a-la-moyenne" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-predictions-marginales-a-la-moyenne-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-a-la-moyenne-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-4" data-glightbox="description: .lightbox-desc-4"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-a-la-moyenne-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-a-la-moyenne-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-4" data-gallery="quarto-lightbox-gallery-4"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-a-la-moyenne-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-marginales-a-la-moyenne-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.4: Prédictions marginales à la moyenne
@@ -2756,7 +2756,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
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+<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-a-la-moyenne-2-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-5" data-gallery="quarto-lightbox-gallery-5"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-a-la-moyenne-2-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-marginales-a-la-moyenne-2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.5: Prédictions marginales à la moyenne
@@ -3411,7 +3411,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-predictions-marginales-effects" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-predictions-marginales-effects-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
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+<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-effects-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-6" data-gallery="quarto-lightbox-gallery-6"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-effects-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-marginales-effects-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.6: Prédictions marginales à la moyenne avec le package effects
@@ -3430,7 +3430,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-predictions-marginales-effects-2" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
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-<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-effects-2-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-7" data-glightbox="description: .lightbox-desc-7"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-effects-2-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="estimations-marginales_files/figure-html/fig-predictions-marginales-effects-2-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-7" data-gallery="quarto-lightbox-gallery-7"><img src="estimations-marginales_files/figure-html/fig-predictions-marginales-effects-2-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-marginales-effects-2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.7: Prédictions marginales à la moyenne avec le package effects
@@ -4089,7 +4089,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-ggpredict" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-ggpredict-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="estimations-marginales_files/figure-html/fig-ggpredict-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-8" data-glightbox="description: .lightbox-desc-8"><img src="estimations-marginales_files/figure-html/fig-ggpredict-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="estimations-marginales_files/figure-html/fig-ggpredict-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-8" data-gallery="quarto-lightbox-gallery-8"><img src="estimations-marginales_files/figure-html/fig-ggpredict-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-ggpredict-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.8: Prédictions marginales avec ggpredict()
@@ -4791,7 +4791,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-contrastes-marginaux-moyens" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
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+<a href="estimations-marginales_files/figure-html/fig-contrastes-marginaux-moyens-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-9" data-gallery="quarto-lightbox-gallery-9"><img src="estimations-marginales_files/figure-html/fig-contrastes-marginaux-moyens-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
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 Figure&nbsp;24.9: Contrastes marginaux moyens
@@ -6582,7 +6582,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
 <div id="fig-contrastes-marginaux-a-la-moyenne" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-contrastes-marginaux-a-la-moyenne-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
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+<a href="estimations-marginales_files/figure-html/fig-contrastes-marginaux-a-la-moyenne-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-10" data-gallery="quarto-lightbox-gallery-10"><img src="estimations-marginales_files/figure-html/fig-contrastes-marginaux-a-la-moyenne-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
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 Figure&nbsp;24.10: Contrastes marginaux à la moyenne
@@ -7224,7 +7224,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
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+<a href="estimations-marginales_files/figure-html/fig-effets-marginaux-moyens-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-11" data-gallery="quarto-lightbox-gallery-11"><img src="estimations-marginales_files/figure-html/fig-effets-marginaux-moyens-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-effets-marginaux-moyens-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.11: Effets marginaux moyens
@@ -7863,7 +7863,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 <div class="cell-output-display page-columns page-full">
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+<a href="estimations-marginales_files/figure-html/fig-effets-marginaux-moyens-margins-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-12" data-gallery="quarto-lightbox-gallery-12"><img src="estimations-marginales_files/figure-html/fig-effets-marginaux-moyens-margins-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-effets-marginaux-moyens-margins-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;24.12: Effets marginaux moyens avec margins
@@ -8516,7 +8516,7 @@ <h1 class="title"><span id="sec-estimations-marginales" class="quarto-section-id
 </ul>
 </div>
   </div>
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diff --git a/docs/analyses/ggplot2.html b/docs/analyses/ggplot2.html
index fd92b8f..5bc7371 100644
--- a/docs/analyses/ggplot2.html
+++ b/docs/analyses/ggplot2.html
@@ -582,7 +582,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 <p><a href="https://ggplot2.tidyverse.org">ggplot2</a> nécessite que les données du graphique soient sous la forme d’un tableau de données (<em>data.frame</em> ou <em>tibble</em>) au format <em>tidy</em>, c’est-à-dire avec une ligne par observation et les différentes valeurs à représenter sous forme de variables du tableau.</p>
 <div id="fig-grammaire-graphiques" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-grammaire-graphiques-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
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+<a href="ressources/ggplot-grammar-of-graphics.png" class="lightbox" data-glightbox="description: .lightbox-desc-1" data-gallery="quarto-lightbox-gallery-1"><img src="ressources/ggplot-grammar-of-graphics.png" class="img-fluid figure-img"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-grammaire-graphiques-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.1: La grammaire des graphiques
@@ -606,7 +606,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
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+<a href="ggplot2_files/figure-html/fig-exemple-simple-ggplot2-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-2" data-gallery="quarto-lightbox-gallery-2"><img src="ggplot2_files/figure-html/fig-exemple-simple-ggplot2-1.png" class="img-fluid figure-img" width="672"></a>
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 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-exemple-simple-ggplot2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.2: Un exemple simple de nuage de points avec <code>ggplot2</code>
@@ -664,7 +664,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 <div class="cell-output-display page-columns page-full">
 <div id="fig-exemple-avance-ggplot2" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-exemple-avance-ggplot2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="ggplot2_files/figure-html/fig-exemple-avance-ggplot2-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-3" data-glightbox="description: .lightbox-desc-3"><img src="ggplot2_files/figure-html/fig-exemple-avance-ggplot2-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="ggplot2_files/figure-html/fig-exemple-avance-ggplot2-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-3" data-gallery="quarto-lightbox-gallery-3"><img src="ggplot2_files/figure-html/fig-exemple-avance-ggplot2-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-exemple-avance-ggplot2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.3: Un exemple avancé de nuage de points avec <code>ggplot2</code>
@@ -681,7 +681,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 <span class="header-section-number">17.3</span> Cheatsheet</h2>
 <div id="fig-cheatsheet-ggplot2" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-cheatsheet-ggplot2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf"><span class="lightbox" data-gallery="quarto-lightbox-gallery-4" data-glightbox="description: .lightbox-desc-4"><img src="ressources/data-visualization-cheatsheet-thumbs.png" class="img-fluid figure-img"></span></a>
+<a href="https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf"><span class="lightbox" data-glightbox="description: .lightbox-desc-4" data-gallery="quarto-lightbox-gallery-4"><img src="ressources/data-visualization-cheatsheet-thumbs.png" class="img-fluid figure-img"></span></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-cheatsheet-ggplot2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.4: Cheatsheet ggplot2
@@ -693,7 +693,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 <p>Le package <a href="https://dreamrs.github.io/esquisse/">esquisse</a> propose un <em>addin</em> offrant une interface visuelle pour la création de graphiques <a href="https://ggplot2.tidyverse.org">ggplot2</a>. Après installation du package, on pourra lancer <a href="https://dreamrs.github.io/esquisse/">esquisse</a> directement à partir du menu <em>addins</em> de <strong>RStudio</strong>.</p>
 <div id="fig-lancement-esquisse" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-lancement-esquisse-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="ressources/esquisse-launch-addin.png" class="lightbox" data-gallery="quarto-lightbox-gallery-5" data-glightbox="description: .lightbox-desc-5"><img src="ressources/esquisse-launch-addin.png" class="img-fluid figure-img"></a>
+<a href="ressources/esquisse-launch-addin.png" class="lightbox" data-glightbox="description: .lightbox-desc-5" data-gallery="quarto-lightbox-gallery-5"><img src="ressources/esquisse-launch-addin.png" class="img-fluid figure-img"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-lancement-esquisse-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.5: Lancement d’<code>esquisse</code> à partir du menu <em>Addins</em> de <strong>RStudio</strong>
@@ -702,7 +702,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 <p>Au lancement de l’<em>addin</em>, une interface permettra de choisir le tableau de données à partir duquel générer le graphique. Le plus simple est de choisir un tableau présent dans l’environnement. Mais <a href="https://dreamrs.github.io/esquisse/">esquisse</a> offre aussi la possibilité d’importer des fichiers externes, voir de procéder à quelques modifications des données.</p>
 <div id="fig-esquisse-import-donnees" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-esquisse-import-donnees-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="ressources/esquisse-import-data.png" class="lightbox" data-gallery="quarto-lightbox-gallery-6" data-glightbox="description: .lightbox-desc-6"><img src="ressources/esquisse-import-data.png" class="img-fluid figure-img"></a>
+<a href="ressources/esquisse-import-data.png" class="lightbox" data-glightbox="description: .lightbox-desc-6" data-gallery="quarto-lightbox-gallery-6"><img src="ressources/esquisse-import-data.png" class="img-fluid figure-img"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-esquisse-import-donnees-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.6: Import de données au lancement d’<code>esquisse</code>
@@ -711,7 +711,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 <p>Le principe général d’<a href="https://dreamrs.github.io/esquisse/">esquisse</a> consiste à associer des variables à des esthétiques par glisser/déposer<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a>. L’outil déterminera automatiquement une géométrie adaptée en fonction de la nature des variables (continues ou catégorielles). Un clic sur le nom de la géométrie en haut à gauche permet de sélectionner une autre géométrie.</p>
 <div class="no-row-height column-margin column-container"><div id="fn2"><p><sup>2</sup>&nbsp;Si une esthétique n’est pas visible à l’écran, on pourra cliquer en haut à droite sur l’icône en forme de roue dentée afin de choisir d’afficher plus d’esthétiques.</p></div></div><div id="fig-esquisse-géométrie" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-esquisse-géométrie-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="ressources/esquisse-geometries.png" class="lightbox" data-gallery="quarto-lightbox-gallery-7" data-glightbox="description: .lightbox-desc-7"><img src="ressources/esquisse-geometries.png" class="img-fluid figure-img"></a>
+<a href="ressources/esquisse-geometries.png" class="lightbox" data-glightbox="description: .lightbox-desc-7" data-gallery="quarto-lightbox-gallery-7"><img src="ressources/esquisse-geometries.png" class="img-fluid figure-img"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-esquisse-géométrie-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.7: Choix d’une géométrie dans <code>esquisse</code>
@@ -721,7 +721,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 <p>Le menu <strong>Code</strong> permet de récupérer le code correspondant au graphique afin de pouvoir le copier/coller dans un script.</p>
 <div id="fig-esquisse-code" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-esquisse-code-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="ressources/esquisse-controls-code.png" class="lightbox" data-gallery="quarto-lightbox-gallery-8" data-glightbox="description: .lightbox-desc-8"><img src="ressources/esquisse-controls-code.png" class="img-fluid figure-img"></a>
+<a href="ressources/esquisse-controls-code.png" class="lightbox" data-glightbox="description: .lightbox-desc-8" data-gallery="quarto-lightbox-gallery-8"><img src="ressources/esquisse-controls-code.png" class="img-fluid figure-img"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-esquisse-code-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;17.8: Obtenir le code du graphique obtenu avec <code>esquisse</code>
@@ -1462,7 +1462,7 @@ <h1 class="title"><span id="sec-ggplot2" class="quarto-section-identifier"><span
 </ul>
 </div>
   </div>
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+</footer><script>var lightboxQuarto = GLightbox({"closeEffect":"zoom","descPosition":"bottom","loop":false,"selector":".lightbox","openEffect":"zoom"});
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diff --git a/docs/analyses/interactions.html b/docs/analyses/interactions.html
index 9a70bb1..7896d22 100644
--- a/docs/analyses/interactions.html
+++ b/docs/analyses/interactions.html
@@ -1234,7 +1234,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
 <div id="fig-predictions-modele-simple" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-predictions-modele-simple-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="interactions_files/figure-html/fig-predictions-modele-simple-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1" data-glightbox="description: .lightbox-desc-1"><img src="interactions_files/figure-html/fig-predictions-modele-simple-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-predictions-modele-simple-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-1" data-gallery="quarto-lightbox-gallery-1"><img src="interactions_files/figure-html/fig-predictions-modele-simple-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-modele-simple-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;26.1: Prédictions marginales moyennes du modèle simple
@@ -1263,7 +1263,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
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-<a href="interactions_files/figure-html/fig-predictions-modele-interaction-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-2" data-glightbox="description: .lightbox-desc-2"><img src="interactions_files/figure-html/fig-predictions-modele-interaction-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-predictions-modele-interaction-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-2" data-gallery="quarto-lightbox-gallery-2"><img src="interactions_files/figure-html/fig-predictions-modele-interaction-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-predictions-modele-interaction-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;26.2: Prédictions marginales moyennes du modèle avec interaction
@@ -1958,7 +1958,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
 <div id="fig-coefficients-modele-interaction" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-coefficients-modele-interaction-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="interactions_files/figure-html/fig-coefficients-modele-interaction-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-4" data-glightbox="description: .lightbox-desc-4"><img src="interactions_files/figure-html/fig-coefficients-modele-interaction-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-coefficients-modele-interaction-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-4" data-gallery="quarto-lightbox-gallery-4"><img src="interactions_files/figure-html/fig-coefficients-modele-interaction-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-coefficients-modele-interaction-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;26.3: Coefficients (odds ratio) du modèle avec interaction
@@ -1986,7 +1986,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
 <div id="fig-interpretation-femme-60ans" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-interpretation-femme-60ans-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="interactions_files/figure-html/fig-interpretation-femme-60ans-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-5" data-glightbox="description: .lightbox-desc-5"><img src="interactions_files/figure-html/fig-interpretation-femme-60ans-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-interpretation-femme-60ans-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-5" data-gallery="quarto-lightbox-gallery-5"><img src="interactions_files/figure-html/fig-interpretation-femme-60ans-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-interpretation-femme-60ans-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;26.4: Représentation graphique de l’estimation de la probabilité de faire du sport pour une femme de 60 ans
@@ -2008,7 +2008,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
 <div id="fig-interpretation-homme-20ans" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-interpretation-homme-20ans-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="interactions_files/figure-html/fig-interpretation-homme-20ans-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-6" data-glightbox="description: .lightbox-desc-6"><img src="interactions_files/figure-html/fig-interpretation-homme-20ans-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-interpretation-homme-20ans-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-6" data-gallery="quarto-lightbox-gallery-6"><img src="interactions_files/figure-html/fig-interpretation-homme-20ans-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-interpretation-homme-20ans-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;26.5: Représentation graphique de l’estimation de la probabilité de faire du sport pour un homme de 20 ans
@@ -2029,7 +2029,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
 <div id="fig-interpretation-homme-60ans" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-interpretation-homme-60ans-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="interactions_files/figure-html/fig-interpretation-homme-60ans-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-7" data-glightbox="description: .lightbox-desc-7"><img src="interactions_files/figure-html/fig-interpretation-homme-60ans-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-interpretation-homme-60ans-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-7" data-gallery="quarto-lightbox-gallery-7"><img src="interactions_files/figure-html/fig-interpretation-homme-60ans-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-interpretation-homme-60ans-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;26.6: Représentation graphique de l’estimation de la probabilité de faire du sport pour un homme de 60 ans
@@ -2082,7 +2082,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
 <div id="fig-comparaison-predictions-marginales-interaction" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-comparaison-predictions-marginales-interaction-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="interactions_files/figure-html/fig-comparaison-predictions-marginales-interaction-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-8" data-glightbox="description: .lightbox-desc-8"><img src="interactions_files/figure-html/fig-comparaison-predictions-marginales-interaction-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-comparaison-predictions-marginales-interaction-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-8" data-gallery="quarto-lightbox-gallery-8"><img src="interactions_files/figure-html/fig-comparaison-predictions-marginales-interaction-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-comparaison-predictions-marginales-interaction-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;26.7: Comparaison des prédictions marginales moyennes des deux modèles avec interaction
@@ -2097,7 +2097,7 @@ <h1 class="title"><span id="sec-interactions" class="quarto-section-identifier">
 <div class="cell-output-display page-columns page-full">
 <div id="fig-coefficients-modele-interaction-3" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
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-<a href="interactions_files/figure-html/fig-coefficients-modele-interaction-3-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-9" data-glightbox="description: .lightbox-desc-9"><img src="interactions_files/figure-html/fig-coefficients-modele-interaction-3-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="interactions_files/figure-html/fig-coefficients-modele-interaction-3-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-9" data-gallery="quarto-lightbox-gallery-9"><img src="interactions_files/figure-html/fig-coefficients-modele-interaction-3-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
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 Figure&nbsp;26.8: Coefficients (odds ratio) du modèle avec interaction simple entre le sexe et le groupe d’âges
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 Figure&nbsp;26.9: Représentation graphique de l’estimation de la probabilité de faire du sport pour un homme de 60 ans (interaction simple)
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 Figure&nbsp;26.10: Prédictions marginales moyennes du modèle avec deux interactions
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 Figure&nbsp;27.1: Représentation graphique des FIV d’un modèle
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 Figure&nbsp;22.1: Facteurs associés à la pratique d’un sport (<em>forest plot</em>)
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 Figure&nbsp;22.2: Facteurs associés à la pratique d’un sport (<em>forest plot</em> avec table des coefficients)
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 Figure&nbsp;22.3: Facteurs associés à la pratique d’un sport avec modelplot()
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 Figure&nbsp;22.4: Odds Ratios associés à la pratique d’un sport avec modelplot()
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 Figure&nbsp;22.5: Facteurs associés à la pratique d’un sport (<em>pairwise contrasts</em>)
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   font-size: 125%;
   font-weight: initial;
@@ -1153,7 +1153,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-bottom-width: 0;
 }
 
-#jddlkducpu .gt_subtitle {
+#gbfmnnnulo .gt_subtitle {
   color: #333333;
   font-size: 85%;
   font-weight: initial;
@@ -1165,7 +1165,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-top-width: 0;
 }
 
-#jddlkducpu .gt_heading {
+#gbfmnnnulo .gt_heading {
   background-color: #FFFFFF;
   text-align: center;
   border-bottom-color: #FFFFFF;
@@ -1177,13 +1177,13 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-right-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_bottom_border {
+#gbfmnnnulo .gt_bottom_border {
   border-bottom-style: solid;
   border-bottom-width: 2px;
   border-bottom-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_col_headings {
+#gbfmnnnulo .gt_col_headings {
   border-top-style: solid;
   border-top-width: 2px;
   border-top-color: #D3D3D3;
@@ -1198,7 +1198,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-right-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_col_heading {
+#gbfmnnnulo .gt_col_heading {
   color: #333333;
   background-color: #FFFFFF;
   font-size: 100%;
@@ -1218,7 +1218,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   overflow-x: hidden;
 }
 
-#jddlkducpu .gt_column_spanner_outer {
+#gbfmnnnulo .gt_column_spanner_outer {
   color: #333333;
   background-color: #FFFFFF;
   font-size: 100%;
@@ -1230,15 +1230,15 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   padding-right: 4px;
 }
 
-#jddlkducpu .gt_column_spanner_outer:first-child {
+#gbfmnnnulo .gt_column_spanner_outer:first-child {
   padding-left: 0;
 }
 
-#jddlkducpu .gt_column_spanner_outer:last-child {
+#gbfmnnnulo .gt_column_spanner_outer:last-child {
   padding-right: 0;
 }
 
-#jddlkducpu .gt_column_spanner {
+#gbfmnnnulo .gt_column_spanner {
   border-bottom-style: solid;
   border-bottom-width: 2px;
   border-bottom-color: #D3D3D3;
@@ -1250,11 +1250,11 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   width: 100%;
 }
 
-#jddlkducpu .gt_spanner_row {
+#gbfmnnnulo .gt_spanner_row {
   border-bottom-style: hidden;
 }
 
-#jddlkducpu .gt_group_heading {
+#gbfmnnnulo .gt_group_heading {
   padding-top: 8px;
   padding-bottom: 8px;
   padding-left: 5px;
@@ -1280,7 +1280,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   text-align: left;
 }
 
-#jddlkducpu .gt_empty_group_heading {
+#gbfmnnnulo .gt_empty_group_heading {
   padding: 0.5px;
   color: #333333;
   background-color: #FFFFFF;
@@ -1295,15 +1295,15 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   vertical-align: middle;
 }
 
-#jddlkducpu .gt_from_md > :first-child {
+#gbfmnnnulo .gt_from_md > :first-child {
   margin-top: 0;
 }
 
-#jddlkducpu .gt_from_md > :last-child {
+#gbfmnnnulo .gt_from_md > :last-child {
   margin-bottom: 0;
 }
 
-#jddlkducpu .gt_row {
+#gbfmnnnulo .gt_row {
   padding-top: 8px;
   padding-bottom: 8px;
   padding-left: 5px;
@@ -1322,7 +1322,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   overflow-x: hidden;
 }
 
-#jddlkducpu .gt_stub {
+#gbfmnnnulo .gt_stub {
   color: #333333;
   background-color: #FFFFFF;
   font-size: 100%;
@@ -1335,7 +1335,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   padding-right: 5px;
 }
 
-#jddlkducpu .gt_stub_row_group {
+#gbfmnnnulo .gt_stub_row_group {
   color: #333333;
   background-color: #FFFFFF;
   font-size: 100%;
@@ -1349,15 +1349,15 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   vertical-align: top;
 }
 
-#jddlkducpu .gt_row_group_first td {
+#gbfmnnnulo .gt_row_group_first td {
   border-top-width: 2px;
 }
 
-#jddlkducpu .gt_row_group_first th {
+#gbfmnnnulo .gt_row_group_first th {
   border-top-width: 2px;
 }
 
-#jddlkducpu .gt_summary_row {
+#gbfmnnnulo .gt_summary_row {
   color: #333333;
   background-color: #FFFFFF;
   text-transform: inherit;
@@ -1367,16 +1367,16 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   padding-right: 5px;
 }
 
-#jddlkducpu .gt_first_summary_row {
+#gbfmnnnulo .gt_first_summary_row {
   border-top-style: solid;
   border-top-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_first_summary_row.thick {
+#gbfmnnnulo .gt_first_summary_row.thick {
   border-top-width: 2px;
 }
 
-#jddlkducpu .gt_last_summary_row {
+#gbfmnnnulo .gt_last_summary_row {
   padding-top: 8px;
   padding-bottom: 8px;
   padding-left: 5px;
@@ -1386,7 +1386,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-bottom-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_grand_summary_row {
+#gbfmnnnulo .gt_grand_summary_row {
   color: #333333;
   background-color: #FFFFFF;
   text-transform: inherit;
@@ -1396,7 +1396,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   padding-right: 5px;
 }
 
-#jddlkducpu .gt_first_grand_summary_row {
+#gbfmnnnulo .gt_first_grand_summary_row {
   padding-top: 8px;
   padding-bottom: 8px;
   padding-left: 5px;
@@ -1406,7 +1406,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-top-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_last_grand_summary_row_top {
+#gbfmnnnulo .gt_last_grand_summary_row_top {
   padding-top: 8px;
   padding-bottom: 8px;
   padding-left: 5px;
@@ -1416,11 +1416,11 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-bottom-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_striped {
+#gbfmnnnulo .gt_striped {
   background-color: rgba(128, 128, 128, 0.05);
 }
 
-#jddlkducpu .gt_table_body {
+#gbfmnnnulo .gt_table_body {
   border-top-style: solid;
   border-top-width: 2px;
   border-top-color: #D3D3D3;
@@ -1429,7 +1429,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-bottom-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_footnotes {
+#gbfmnnnulo .gt_footnotes {
   color: #333333;
   background-color: #FFFFFF;
   border-bottom-style: none;
@@ -1443,7 +1443,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-right-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_footnote {
+#gbfmnnnulo .gt_footnote {
   margin: 0px;
   font-size: 90%;
   padding-top: 4px;
@@ -1452,7 +1452,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   padding-right: 5px;
 }
 
-#jddlkducpu .gt_sourcenotes {
+#gbfmnnnulo .gt_sourcenotes {
   color: #333333;
   background-color: #FFFFFF;
   border-bottom-style: none;
@@ -1466,7 +1466,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   border-right-color: #D3D3D3;
 }
 
-#jddlkducpu .gt_sourcenote {
+#gbfmnnnulo .gt_sourcenote {
   font-size: 90%;
   padding-top: 4px;
   padding-bottom: 4px;
@@ -1474,72 +1474,72 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
   padding-right: 5px;
 }
 
-#jddlkducpu .gt_left {
+#gbfmnnnulo .gt_left {
   text-align: left;
 }
 
-#jddlkducpu .gt_center {
+#gbfmnnnulo .gt_center {
   text-align: center;
 }
 
-#jddlkducpu .gt_right {
+#gbfmnnnulo .gt_right {
   text-align: right;
   font-variant-numeric: tabular-nums;
 }
 
-#jddlkducpu .gt_font_normal {
+#gbfmnnnulo .gt_font_normal {
   font-weight: normal;
 }
 
-#jddlkducpu .gt_font_bold {
+#gbfmnnnulo .gt_font_bold {
   font-weight: bold;
 }
 
-#jddlkducpu .gt_font_italic {
+#gbfmnnnulo .gt_font_italic {
   font-style: italic;
 }
 
-#jddlkducpu .gt_super {
+#gbfmnnnulo .gt_super {
   font-size: 65%;
 }
 
-#jddlkducpu .gt_footnote_marks {
+#gbfmnnnulo .gt_footnote_marks {
   font-size: 75%;
   vertical-align: 0.4em;
   position: initial;
 }
 
-#jddlkducpu .gt_asterisk {
+#gbfmnnnulo .gt_asterisk {
   font-size: 100%;
   vertical-align: 0;
 }
 
-#jddlkducpu .gt_indent_1 {
+#gbfmnnnulo .gt_indent_1 {
   text-indent: 5px;
 }
 
-#jddlkducpu .gt_indent_2 {
+#gbfmnnnulo .gt_indent_2 {
   text-indent: 10px;
 }
 
-#jddlkducpu .gt_indent_3 {
+#gbfmnnnulo .gt_indent_3 {
   text-indent: 15px;
 }
 
-#jddlkducpu .gt_indent_4 {
+#gbfmnnnulo .gt_indent_4 {
   text-indent: 20px;
 }
 
-#jddlkducpu .gt_indent_5 {
+#gbfmnnnulo .gt_indent_5 {
   text-indent: 25px;
 }
 
-#jddlkducpu .katex-display {
+#gbfmnnnulo .katex-display {
   display: inline-flex !important;
   margin-bottom: 0.75em !important;
 }
 
-#jddlkducpu div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
+#gbfmnnnulo div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after {
   height: 0px !important;
 }
 </style>
@@ -1790,13 +1790,13 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
 <p>Pour automatiser l’ensemble de ce processus, on peut copier/coller le code de la fonction générique suivante<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>&nbsp;:</p>
 <div class="cell">
 <div class="sourceCode cell-code" id="cb45"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb45-1"><a href="#cb45-1"></a>step_with_na <span class="ot">&lt;-</span> <span class="cf">function</span>(model,</span>
-<span id="cb45-2"><a href="#cb45-2"></a>                         <span class="at">full_data =</span> <span class="cn">NULL</span>, ...) {</span>
-<span id="cb45-3"><a href="#cb45-3"></a>  <span class="co"># data with no NAs</span></span>
-<span id="cb45-4"><a href="#cb45-4"></a>  <span class="cf">if</span> (<span class="fu">is.null</span>(full_data)) {</span>
-<span id="cb45-5"><a href="#cb45-5"></a>    ...data_no_na <span class="ot">&lt;-</span> <span class="fu">model.frame</span>(model)</span>
-<span id="cb45-6"><a href="#cb45-6"></a>  } <span class="cf">else</span> {</span>
-<span id="cb45-7"><a href="#cb45-7"></a>    ...data_no_na <span class="ot">&lt;-</span> <span class="fu">get_all_vars</span>(model, <span class="at">data =</span> full_data)</span>
-<span id="cb45-8"><a href="#cb45-8"></a>    ...data_no_na <span class="ot">&lt;-</span> ...data_no_na[<span class="fu">complete.cases</span>(...data_no_na), ]</span>
+<span id="cb45-2"><a href="#cb45-2"></a>                         <span class="at">full_data =</span> <span class="fu">eval</span>(model<span class="sc">$</span>call<span class="sc">$</span>data),</span>
+<span id="cb45-3"><a href="#cb45-3"></a>                         ...) {</span>
+<span id="cb45-4"><a href="#cb45-4"></a>  <span class="co"># data with no NAs</span></span>
+<span id="cb45-5"><a href="#cb45-5"></a>  <span class="cf">if</span> (<span class="fu">is.null</span>(full_data)) {</span>
+<span id="cb45-6"><a href="#cb45-6"></a>    ...data_no_na <span class="ot">&lt;-</span> <span class="fu">model.frame</span>(model)</span>
+<span id="cb45-7"><a href="#cb45-7"></a>  } <span class="cf">else</span> {</span>
+<span id="cb45-8"><a href="#cb45-8"></a>    ...data_no_na <span class="ot">&lt;-</span> <span class="fu">get_all_vars</span>(model, <span class="at">data =</span> full_data) <span class="sc">|&gt;</span> <span class="fu">na.omit</span>()</span>
 <span id="cb45-9"><a href="#cb45-9"></a>  }</span>
 <span id="cb45-10"><a href="#cb45-10"></a>  </span>
 <span id="cb45-11"><a href="#cb45-11"></a>  <span class="co"># assign ...data_no_na in parent.frame()</span></span>
@@ -1827,7 +1827,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
 <span id="cb45-36"><a href="#cb45-36"></a>  }</span>
 <span id="cb45-37"><a href="#cb45-37"></a>}</span></code><button title="Copier vers le presse-papier" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<p>Elle réalise l’ensemble des opérations décrites plus haut en profitant de la flexibilité offerte par la fonction <code><a href="https://rdrr.io/r/stats/update.html">update()</a></code>. La fonction <code><a href="https://rdrr.io/r/stats/model.frame.html">model.frame()</a></code> permet de récupérer le jeu de données utilisé par un modèle (et dans lequel les lignes incomplètes ont été supprimées). La fonction <code><a href="https://rdrr.io/r/stats/terms.html">terms()</a></code> permet de récupérer l’équation du modèle.</p>
+<p>Elle réalise l’ensemble des opérations décrites plus haut en profitant de la flexibilité offerte par la fonction <code><a href="https://rdrr.io/r/stats/update.html">update()</a></code>. La fonction <code><a href="https://rdrr.io/r/stats/terms.html">terms()</a></code> permet de récupérer l’équation du modèle. La fonction <code><a href="https://rdrr.io/r/stats/model.frame.html">model.frame()</a></code> permet de récupérer le jeu de données utilisé par un modèle (et dans lequel les lignes incomplètes ont été supprimées), mais cela ne marchera que si c’est un modèle simple (chaque terme du modèle est une variable directe du tableau de données et non une variable calculée). Sinon, on peut appeler <code>step_with_na()</code> en lui passant en plus le tableau de données original. Cela permet d’avoir recours à la fonction <code><a href="https://rdrr.io/r/stats/model.frame.html">get_all_vars()</a></code> qui permet d’extraire d’un tableau de données toutes les variables nécessaires au calcul d’un modèle.</p>
 <p><strong>Attention :</strong> il s’agit d’une fonction expérimentale et elle n’est peut-être pas compatible avec tous les types de modèles. Elle a été testée avec les modèles <code><a href="https://rdrr.io/r/stats/lm.html">lm()</a></code>, <code><a href="https://rdrr.io/r/stats/glm.html">glm()</a></code> et <code><a href="https://rdrr.io/pkg/nnet/man/multinom.html">nnet::multinom()</a></code>.</p>
 <div class="cell">
 <div class="sourceCode cell-code" id="cb46"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb46-1"><a href="#cb46-1"></a>mod_na_reduit_direct <span class="ot">&lt;-</span> <span class="fu">step_with_na</span>(mod_na, <span class="at">trace =</span> <span class="dv">0</span>)</span></code><button title="Copier vers le presse-papier" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -2462,7 +2462,7 @@ <h1 class="title"><span id="sec-selection-modele-pas-a-pas" class="quarto-sectio
 </ul>
 </div>
   </div>
-</footer><script>var lightboxQuarto = GLightbox({"descPosition":"bottom","selector":".lightbox","closeEffect":"zoom","loop":false,"openEffect":"zoom"});
+</footer><script>var lightboxQuarto = GLightbox({"openEffect":"zoom","closeEffect":"zoom","descPosition":"bottom","selector":".lightbox","loop":false});
 window.onload = () => {
   lightboxQuarto.on('slide_before_load', (data) => {
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diff --git a/docs/analyses/statistique-bivariee.html b/docs/analyses/statistique-bivariee.html
index 3ddf987..aa590e3 100644
--- a/docs/analyses/statistique-bivariee.html
+++ b/docs/analyses/statistique-bivariee.html
@@ -2289,7 +2289,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
 <div class="cell-output-display page-columns page-full">
 <div id="fig-bar-fill" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-bar-fill-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="statistique-bivariee_files/figure-html/fig-bar-fill-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-1" data-glightbox="description: .lightbox-desc-1"><img src="statistique-bivariee_files/figure-html/fig-bar-fill-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="statistique-bivariee_files/figure-html/fig-bar-fill-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-1" data-gallery="quarto-lightbox-gallery-1"><img src="statistique-bivariee_files/figure-html/fig-bar-fill-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-bar-fill-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;19.1: un graphique en barres croisant deux variables
@@ -2307,7 +2307,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
 <div class="cell-output-display page-columns page-full">
 <div id="fig-bar-fill-dodge" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-bar-fill-dodge-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-2" data-glightbox="description: .lightbox-desc-2"><img src="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-2" data-gallery="quarto-lightbox-gallery-2"><img src="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-bar-fill-dodge-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;19.2: un graphique avec des barres côte à côte
@@ -2326,7 +2326,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
 <div class="cell-output-display page-columns page-full">
 <div id="fig-bar-fill-dodge-2" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
 <figure class="quarto-float quarto-float-fig figure page-columns page-full"><div aria-describedby="fig-bar-fill-dodge-2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
-<a href="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-2-1.png" class="lightbox" data-gallery="quarto-lightbox-gallery-3" data-glightbox="description: .lightbox-desc-3"><img src="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-2-1.png" class="img-fluid figure-img" width="672"></a>
+<a href="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-2-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-3" data-gallery="quarto-lightbox-gallery-3"><img src="statistique-bivariee_files/figure-html/fig-bar-fill-dodge-2-1.png" class="img-fluid figure-img" width="672"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-bar-fill-dodge-2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;19.3: un graphique en barres cumulées
@@ -7022,7 +7022,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
 <div class="cell-output-display page-columns page-full">
 <div id="fig-geom_boxplot" class="quarto-figure quarto-figure-center quarto-float anchored page-columns page-full">
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 Figure&nbsp;19.4: boîtes à moustache
@@ -7052,7 +7052,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 Figure&nbsp;19.5: graphique en violons
@@ -7069,7 +7069,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 </div>
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 Figure&nbsp;19.6: un nuage de points avec une variable continue et une variable catégorielle
@@ -7090,7 +7090,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 </div>
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 Figure&nbsp;19.7: un nuage de points avec une variable continue et une variable catégorielle et avec un décalage horizontal aléatoire
@@ -7107,7 +7107,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 Figure&nbsp;19.8: âge moyen selon le grade
@@ -7126,7 +7126,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-stat_weighted_mean-2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;19.9: âge moyen selon le grade, par traitement et état d’avancement de la maladie
@@ -9390,7 +9390,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 Figure&nbsp;19.10: nuage de points
@@ -9408,7 +9408,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
 <div class="cell-output-display page-columns page-full">
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 Figure&nbsp;19.11: nuage de points avec une courbe de tendance
@@ -9426,7 +9426,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
 <div class="cell-output-display page-columns page-full">
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 Figure&nbsp;19.12: nuage de points avec droite de régression linéaire
@@ -9519,7 +9519,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 Figure&nbsp;19.13: nuage de points avec représentation synthétique des densités marginales
@@ -10070,7 +10070,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-ggpairs-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;19.14: une matrice de corrélation avec ggpairs()
@@ -10084,7 +10084,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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+<a href="statistique-bivariee_files/figure-html/fig-ggpairs-2-1.png" class="lightbox" data-glightbox="description: .lightbox-desc-23" data-gallery="quarto-lightbox-gallery-23"><img src="statistique-bivariee_files/figure-html/fig-ggpairs-2-1.png" class="img-fluid figure-img" width="1536"></a>
 </div>
 <figcaption class="quarto-float-caption-margin quarto-float-caption quarto-float-fig margin-caption" id="fig-ggpairs-2-caption-0ceaefa1-69ba-4598-a22c-09a6ac19f8ca">
 Figure&nbsp;19.15: un second example de matrice de corrélation
@@ -10724,7 +10724,7 @@ <h1 class="title"><span id="sec-statistique-bivariee" class="quarto-section-iden
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 Figure&nbsp;18.1: un histogramme simple
@@ -657,7 +657,7 @@ <h1 class="title"><span id="sec-statistique-univariee" class="quarto-section-ide
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 Figure&nbsp;18.2: un histogramme personnalisé
@@ -673,7 +673,7 @@ <h1 class="title"><span id="sec-statistique-univariee" class="quarto-section-ide
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 Figure&nbsp;18.3: un histogramme en 10 classes
@@ -689,7 +689,7 @@ <h1 class="title"><span id="sec-statistique-univariee" class="quarto-section-ide
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 Figure&nbsp;18.4: une courbe de densité
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 Figure&nbsp;18.5: un diagramme en barres simple
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 Figure&nbsp;18.6: un diagramme en barres épuré
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 Figure&nbsp;18.7: un diagramme en barres épuré
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 Figure&nbsp;40.1: Capture d’écran de l’interface d’<code>explor</code>
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 Figure&nbsp;40.2: Représentation graphique de la variance expliquée par les différents axes de l’ACM
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 Figure&nbsp;40.3: Contribution des modalités au premier axe
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 Figure&nbsp;40.4: Contribution des modalités au deuxième axe
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 Figure&nbsp;40.5: Projection des modalités dans le plan factoriel
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 Figure&nbsp;40.6: Projection des individus dans le plan factoriel
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 Figure&nbsp;40.7: Projection des individus dans le plan factoriel
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 Figure&nbsp;40.8: Projection des individus dans le plan factoriel selon la pratique d’un sport
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 Figure&nbsp;40.9: Projection des modalités dans le plan factoriel (incluant les variables additionnelles)
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 Figure&nbsp;40.10: Inertie expliquée par axe (comparaison des ACM réalisées avec ade4 et FactoMineR)
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diff --git a/docs/search.json b/docs/search.json
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@@ -1408,7 +1408,7 @@
     "href": "analyses/selection-modele-pas-a-pas.html#sec-step-avec-na",
     "title": "23  Sélection pas à pas d’un modèle réduit",
     "section": "\n23.8 Sélection pas à pas et valeurs manquantes",
-    "text": "23.8 Sélection pas à pas et valeurs manquantes\nSi certaines de nos variables explications contiennent des valeurs manquantes (NA), cela peut entraîner des erreurs au moment d’avoir recours à step(), car le nombre d’observations dans le modèle va changer si on retire du modèle une variable explicative avec des valeurs manquantes.\nPrenons un exemple, en ajoutant des valeurs manquantes à la variable relig (pour cela nous allons recoder les refus et les ne sait pas en NA).\n\nd$relig_na &lt;- \n  d$relig |&gt; \n  fct_recode(\n    NULL = \"Rejet\",\n    NULL = \"NSP ou NVPR\"\n  )\n\nmod_na &lt;- glm(\n  sport ~ sexe + groupe_ages + etudes + relig_na + lecture.bd,\n  family = binomial,\n  data = d\n)\n\nAu moment d’exécuter step() nous obtenons l’erreur mentionnée précédemment.\n\nstep(mod_na)\n\nStart:  AIC=2096.64\nsport ~ sexe + groupe_ages + etudes + relig_na + lecture.bd\n\n              Df Deviance    AIC\n- relig_na     3   2073.2 2093.2\n- lecture.bd   1   2072.2 2096.2\n&lt;none&gt;             2070.6 2096.6\n- sexe         1   2088.6 2112.6\n- groupe_ages  3   2118.0 2138.0\n- etudes       4   2218.1 2236.1\n\n\nError in step(mod_na): le nombre de lignes utilisées a changé : supprimer les valeurs manquantes ?\n\n\nPas d’inquiétude ! Il y a moyen de s’en sortir en adoptant la stratégie suivante :\n\ncréer une copie du jeu de données avec uniquement des observations sans valeur manquante pour nos variables explicatives ;\ncalculer notre modèle complet à partir de ce jeu de données ;\nappliquer step() ;\nrecalculer le modèle réduit en repartant du jeu de données complet.\n\nPremière étape, ne garder que les observations complètes à l’aide de tidyr::drop_na(), en lui indiquant la liste des variables dans lesquelles vérifier la présence ou non de NA.\n\nd_complet &lt;- d |&gt; \n  drop_na(sexe, groupe_ages, etudes, relig_na, lecture.bd)\n\nDeuxième étape, calculons le modèle complet avec ce jeu données.\n\nmod_na_alt &lt;- glm(\n  sport ~ sexe + groupe_ages + etudes + relig_na +lecture.bd,\n  family = binomial,\n  data = d_complet\n)\n\nLe modèle mod_na_alt est tout à fait identique au modèle mod_na, car glm() supprime de lui-même les valeurs manquantes quand elles existent. Nous pouvons maintenant utiliser step().\n\nmod_na_reduit &lt;- step(mod_na_alt)\n\nStart:  AIC=2096.64\nsport ~ sexe + groupe_ages + etudes + relig_na + lecture.bd\n\n              Df Deviance    AIC\n- relig_na     3   2073.2 2093.2\n- lecture.bd   1   2072.2 2096.2\n&lt;none&gt;             2070.6 2096.6\n- sexe         1   2088.6 2112.6\n- groupe_ages  3   2118.0 2138.0\n- etudes       4   2218.1 2236.1\n\nStep:  AIC=2093.19\nsport ~ sexe + groupe_ages + etudes + lecture.bd\n\n              Df Deviance    AIC\n- lecture.bd   1   2074.6 2092.6\n&lt;none&gt;             2073.2 2093.2\n- sexe         1   2090.2 2108.2\n- groupe_ages  3   2118.5 2132.5\n- etudes       4   2221.4 2233.4\n\nStep:  AIC=2092.59\nsport ~ sexe + groupe_ages + etudes\n\n              Df Deviance    AIC\n&lt;none&gt;             2074.6 2092.6\n- sexe         1   2091.1 2107.1\n- groupe_ages  3   2119.6 2131.6\n- etudes       4   2227.2 2237.2\n\n\nCela s’exécute sans problème car tous les sous-modèles sont calculés à partir de d_complet et donc ont bien le même nombre d’observations. Cependant, dans notre modèle réduit, on a retiré 137 observations en raison d’une valeur manquante sur la variable relig_na, variable qui n’est plus présente dans notre modèle réduit. Il serait donc pertinent de réintégrer ces observations.\nNous allons donc recalculer le modèle réduit mais à partir de d. Inutile de recopier à la main la formule du modèle réduit, car nous pouvons l’obtenir directement avec mod_na_reduit$formula.\n\nmod_na_reduit2 &lt;- glm(\n  mod_na_reduit$formula,\n  family = binomial,\n  data = d\n)\n\nAttention : mod_na_reduit et mod_na_reduit2 ne sont pas identiques puisque le second a été calculé sur un plus grand nombre d’observations, ce qui change très légèrement les valeurs des coefficients.\n\n\n\n\n\n\nAstuce\n\n\n\nPour automatiser l’ensemble de ce processus, on peut copier/coller le code de la fonction générique suivante1 :\n\nstep_with_na &lt;- function(model,\n                         full_data = NULL, ...) {\n  # data with no NAs\n  if (is.null(full_data)) {\n    ...data_no_na &lt;- model.frame(model)\n  } else {\n    ...data_no_na &lt;- get_all_vars(model, data = full_data)\n    ...data_no_na &lt;- ...data_no_na[complete.cases(...data_no_na), ]\n  }\n  \n  # assign ...data_no_na in parent.frame()\n  assign(\"...data_no_na\", ...data_no_na, envir = parent.frame())\n  \n  # refit the model without NAs\n  model_no_na &lt;- update(\n    model,\n    formula = terms(model),\n    data = ...data_no_na\n  )\n  \n  # apply step()\n  model_simplified &lt;- step(model_no_na, ...)\n  \n  # recompute simplified model using full data\n  if (is.null(full_data)) {\n    update(\n      model,\n      formula = terms(model_simplified)\n    )\n  } else {\n    update(\n      model,\n      formula = terms(model_simplified),\n      data = full_data\n    )\n  }\n}\n\nElle réalise l’ensemble des opérations décrites plus haut en profitant de la flexibilité offerte par la fonction update(). La fonction model.frame() permet de récupérer le jeu de données utilisé par un modèle (et dans lequel les lignes incomplètes ont été supprimées). La fonction terms() permet de récupérer l’équation du modèle.\nAttention : il s’agit d’une fonction expérimentale et elle n’est peut-être pas compatible avec tous les types de modèles. Elle a été testée avec les modèles lm(), glm() et nnet::multinom().\n\nmod_na_reduit_direct &lt;- step_with_na(mod_na, trace = 0)\n\nLe résultat obtenu est strictement identique.\n\nanova(mod_na_reduit2, mod_na_reduit_direct)\n\nAnalysis of Deviance Table\n\nModel 1: sport ~ sexe + groupe_ages + etudes\nModel 2: sport ~ sexe + groupe_ages + etudes\n  Resid. Df Resid. Dev Df Deviance Pr(&gt;Chi)\n1      1991     2232.6                     \n2      1991     2232.6  0        0         \n\n\n\n\n\n\n1 L’argument full_data peut-être utile lorsque le jeu de données n’est pas disponible dans l’environnement parent, par exemple lorsque l’on imbrique des calculs avec lapply() ou purrr:map(). On pourra lors passer manuellement le jeu de données complet à la fonction.\nFigure 23.1: Comparaison visuelle des deux modèles (dodge)\nFigure 23.2: Comparaison visuelle des deux modèles (faceted)",
+    "text": "23.8 Sélection pas à pas et valeurs manquantes\nSi certaines de nos variables explications contiennent des valeurs manquantes (NA), cela peut entraîner des erreurs au moment d’avoir recours à step(), car le nombre d’observations dans le modèle va changer si on retire du modèle une variable explicative avec des valeurs manquantes.\nPrenons un exemple, en ajoutant des valeurs manquantes à la variable relig (pour cela nous allons recoder les refus et les ne sait pas en NA).\n\nd$relig_na &lt;- \n  d$relig |&gt; \n  fct_recode(\n    NULL = \"Rejet\",\n    NULL = \"NSP ou NVPR\"\n  )\n\nmod_na &lt;- glm(\n  sport ~ sexe + groupe_ages + etudes + relig_na + lecture.bd,\n  family = binomial,\n  data = d\n)\n\nAu moment d’exécuter step() nous obtenons l’erreur mentionnée précédemment.\n\nstep(mod_na)\n\nStart:  AIC=2096.64\nsport ~ sexe + groupe_ages + etudes + relig_na + lecture.bd\n\n              Df Deviance    AIC\n- relig_na     3   2073.2 2093.2\n- lecture.bd   1   2072.2 2096.2\n&lt;none&gt;             2070.6 2096.6\n- sexe         1   2088.6 2112.6\n- groupe_ages  3   2118.0 2138.0\n- etudes       4   2218.1 2236.1\n\n\nError in step(mod_na): le nombre de lignes utilisées a changé : supprimer les valeurs manquantes ?\n\n\nPas d’inquiétude ! Il y a moyen de s’en sortir en adoptant la stratégie suivante :\n\ncréer une copie du jeu de données avec uniquement des observations sans valeur manquante pour nos variables explicatives ;\ncalculer notre modèle complet à partir de ce jeu de données ;\nappliquer step() ;\nrecalculer le modèle réduit en repartant du jeu de données complet.\n\nPremière étape, ne garder que les observations complètes à l’aide de tidyr::drop_na(), en lui indiquant la liste des variables dans lesquelles vérifier la présence ou non de NA.\n\nd_complet &lt;- d |&gt; \n  drop_na(sexe, groupe_ages, etudes, relig_na, lecture.bd)\n\nDeuxième étape, calculons le modèle complet avec ce jeu données.\n\nmod_na_alt &lt;- glm(\n  sport ~ sexe + groupe_ages + etudes + relig_na +lecture.bd,\n  family = binomial,\n  data = d_complet\n)\n\nLe modèle mod_na_alt est tout à fait identique au modèle mod_na, car glm() supprime de lui-même les valeurs manquantes quand elles existent. Nous pouvons maintenant utiliser step().\n\nmod_na_reduit &lt;- step(mod_na_alt)\n\nStart:  AIC=2096.64\nsport ~ sexe + groupe_ages + etudes + relig_na + lecture.bd\n\n              Df Deviance    AIC\n- relig_na     3   2073.2 2093.2\n- lecture.bd   1   2072.2 2096.2\n&lt;none&gt;             2070.6 2096.6\n- sexe         1   2088.6 2112.6\n- groupe_ages  3   2118.0 2138.0\n- etudes       4   2218.1 2236.1\n\nStep:  AIC=2093.19\nsport ~ sexe + groupe_ages + etudes + lecture.bd\n\n              Df Deviance    AIC\n- lecture.bd   1   2074.6 2092.6\n&lt;none&gt;             2073.2 2093.2\n- sexe         1   2090.2 2108.2\n- groupe_ages  3   2118.5 2132.5\n- etudes       4   2221.4 2233.4\n\nStep:  AIC=2092.59\nsport ~ sexe + groupe_ages + etudes\n\n              Df Deviance    AIC\n&lt;none&gt;             2074.6 2092.6\n- sexe         1   2091.1 2107.1\n- groupe_ages  3   2119.6 2131.6\n- etudes       4   2227.2 2237.2\n\n\nCela s’exécute sans problème car tous les sous-modèles sont calculés à partir de d_complet et donc ont bien le même nombre d’observations. Cependant, dans notre modèle réduit, on a retiré 137 observations en raison d’une valeur manquante sur la variable relig_na, variable qui n’est plus présente dans notre modèle réduit. Il serait donc pertinent de réintégrer ces observations.\nNous allons donc recalculer le modèle réduit mais à partir de d. Inutile de recopier à la main la formule du modèle réduit, car nous pouvons l’obtenir directement avec mod_na_reduit$formula.\n\nmod_na_reduit2 &lt;- glm(\n  mod_na_reduit$formula,\n  family = binomial,\n  data = d\n)\n\nAttention : mod_na_reduit et mod_na_reduit2 ne sont pas identiques puisque le second a été calculé sur un plus grand nombre d’observations, ce qui change très légèrement les valeurs des coefficients.\n\n\n\n\n\n\nAstuce\n\n\n\nPour automatiser l’ensemble de ce processus, on peut copier/coller le code de la fonction générique suivante1 :\n\nstep_with_na &lt;- function(model,\n                         full_data = eval(model$call$data),\n                         ...) {\n  # data with no NAs\n  if (is.null(full_data)) {\n    ...data_no_na &lt;- model.frame(model)\n  } else {\n    ...data_no_na &lt;- get_all_vars(model, data = full_data) |&gt; na.omit()\n  }\n  \n  # assign ...data_no_na in parent.frame()\n  assign(\"...data_no_na\", ...data_no_na, envir = parent.frame())\n  \n  # refit the model without NAs\n  model_no_na &lt;- update(\n    model,\n    formula = terms(model),\n    data = ...data_no_na\n  )\n  \n  # apply step()\n  model_simplified &lt;- step(model_no_na, ...)\n  \n  # recompute simplified model using full data\n  if (is.null(full_data)) {\n    update(\n      model,\n      formula = terms(model_simplified)\n    )\n  } else {\n    update(\n      model,\n      formula = terms(model_simplified),\n      data = full_data\n    )\n  }\n}\n\nElle réalise l’ensemble des opérations décrites plus haut en profitant de la flexibilité offerte par la fonction update(). La fonction terms() permet de récupérer l’équation du modèle. La fonction model.frame() permet de récupérer le jeu de données utilisé par un modèle (et dans lequel les lignes incomplètes ont été supprimées), mais cela ne marchera que si c’est un modèle simple (chaque terme du modèle est une variable directe du tableau de données et non une variable calculée). Sinon, on peut appeler step_with_na() en lui passant en plus le tableau de données original. Cela permet d’avoir recours à la fonction get_all_vars() qui permet d’extraire d’un tableau de données toutes les variables nécessaires au calcul d’un modèle.\nAttention : il s’agit d’une fonction expérimentale et elle n’est peut-être pas compatible avec tous les types de modèles. Elle a été testée avec les modèles lm(), glm() et nnet::multinom().\n\nmod_na_reduit_direct &lt;- step_with_na(mod_na, trace = 0)\n\nLe résultat obtenu est strictement identique.\n\nanova(mod_na_reduit2, mod_na_reduit_direct)\n\nAnalysis of Deviance Table\n\nModel 1: sport ~ sexe + groupe_ages + etudes\nModel 2: sport ~ sexe + groupe_ages + etudes\n  Resid. Df Resid. Dev Df Deviance Pr(&gt;Chi)\n1      1991     2232.6                     \n2      1991     2232.6  0        0         \n\n\n\n\n\n\n1 L’argument full_data peut-être utile lorsque le jeu de données n’est pas disponible dans l’environnement parent, par exemple lorsque l’on imbrique des calculs avec lapply() ou purrr:map(). On pourra lors passer manuellement le jeu de données complet à la fonction.\nFigure 23.1: Comparaison visuelle des deux modèles (dodge)\nFigure 23.2: Comparaison visuelle des deux modèles (faceted)",
     "crumbs": [
       "**Analyses**",
       "<span class='chapter-number'>23</span>  <span class='chapter-title'>Sélection pas à pas d'un modèle réduit</span>"