Le test de Mac Nemar Permet de savoir si deux proportions appari\u00e9es mesur\u00e9es sont identiques ou non.<\/p>\n
\u00a0<\/p>\n
Pour pouvoir r\u00e9aliser ce test il est n\u00e9cessaire d\u2019avoir un \u00e9chantillonnage al\u00e9atoire dans chaque \u00e9chantillon, que chaque effectif soit sup\u00e9rieur ou \u00e9gal \u00e0 5 et que tous les individus passent d\u2019un \u00e9tat \u00e0 l\u2019autre.<\/p>\n
\u00a0<\/p>\n
Pour appliquer le test de Mac Nemar nous utilisons la fonction mcnemar.test().<\/b><\/p>\n
\u00a0<\/p>\n
Exemple :<\/p>\n
Nous nous demandons si la proportion de fumeur\u00a0 a vari\u00e9\u00a0 dans le temps ?<\/p>\n
\n\nmat<-matrix(c(20,2,10,28),2)\n\ndimnames(mat) <- list(\"avant\" = c(\"fumeur\", \"non \u00a0\u00a0 fumeur\"),\"apres\" = c(\"fumeur\", \"non fumeur\"))\n\n\u00a0\n\nmat\n\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 apres\n\navant\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 fumeur non fumeur\n\n\u00a0 fumeur\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 20\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 10\n\n\u00a0 non fumeur\u00a0\u00a0\u00a0\u00a0\u00a0 2\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 28\n\n\u00a0\n\nmcnemar.test(mat)\n\n\u00a0\n\n# \u00a0 \u00a0 \u00a0 \u00a0McNemar's Chi-squared test with continuity correction\n\n\u00a0\n\n#data:\u00a0 mat\n\n#McNemar's chi-squared = 4.0833, df = 1, p-value = 0.04331\n\n<\/code><\/pre>\n\u00a0<\/p>\n
La p-value est inf\u00e9rieure \u00e0 0.05, nous consid\u00e9rons donc que les proportions sont significativement diff\u00e9rentes\u00a0: nous constatons que la proportion de fumeur\u00a0 a donc vari\u00e9\u00a0 dans le temps, nous pouvons ajouter que celle-ci a tendance \u00e0 diminuer.<\/p>\n","protected":false},"excerpt":{"rendered":"
Le test de Mac Nemar Permet de savoir si deux proportions appari\u00e9es mesur\u00e9es sont identiques ou non. \u00a0 Pour pouvoir r\u00e9aliser ce test il est n\u00e9cessaire d\u2019avoir un \u00e9chantillonnage al\u00e9atoire dans chaque \u00e9chantillon, que chaque effectif soit sup\u00e9rieur ou \u00e9gal \u00e0 5 et que tous les individus passent d\u2019un \u00e9tat \u00e0 l\u2019autre. \u00a0 Pour appliquer le test de Mac Nemar nous utilisons la fonction mcnemar.test(). \u00a0 Exemple : Nous nous demandons si la proportion de fumeur\u00a0 a vari\u00e9\u00a0 dans le temps ? mat<-matrix(c(20,2,10,28),2) dimnames(mat) <- list(\u00ab\u00a0avant\u00a0\u00bb = c(\u00ab\u00a0fumeur\u00a0\u00bb, \u00ab\u00a0non \u00a0\u00a0 fumeur\u00a0\u00bb),\u00a0\u00bbapres\u00a0\u00bb = c(\u00ab\u00a0fumeur\u00a0\u00bb, \u00ab\u00a0non fumeur\u00a0\u00bb)) \u00a0 mat \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 apres avant\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 fumeur non fumeur \u00a0 fumeur\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Read More →<\/a><\/p>\n","protected":false},"author":13,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","rop_custom_images_group":[],"rop_custom_messages_group":[],"rop_publish_now":"initial","rop_publish_now_accounts":{"twitter_399453572_399453572":""},"rop_publish_now_history":[],"rop_publish_now_status":"pending","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[21],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-helene","4":"post-3185","6":"format-standard","7":"category-test"},"acf":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9O7Sx-Pn","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3185","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/comments?post=3185"}],"version-history":[{"count":2,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3185\/revisions"}],"predecessor-version":[{"id":4295,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/3185\/revisions\/4295"}],"wp:attachment":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/media?parent=3185"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/categories?post=3185"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/tags?post=3185"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}