<\/p>\n
Tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA,<\/a> her grupta ayn\u0131 deneklerin yer ald\u0131\u011f\u0131 \u00fc\u00e7 veya daha fazla grubun ortalamalar\u0131 aras\u0131nda istatistiksel olarak anlaml\u0131 bir fark olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in kullan\u0131l\u0131r.<\/span><\/p>\n Bu e\u011fitimde Python’da tek y\u00f6nl\u00fc tekrarlanan \u00f6l\u00e7\u00fcm ANOVA’s\u0131n\u0131n nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n Ara\u015ft\u0131rmac\u0131lar d\u00f6rt farkl\u0131 ilac\u0131n farkl\u0131 reaksiyon s\u00fcrelerine neden olup olmad\u0131\u011f\u0131n\u0131 bilmek istiyorlar. Bunu test etmek i\u00e7in be\u015f hastan\u0131n d\u00f6rt farkl\u0131 ilaca reaksiyon s\u00fcrelerini \u00f6l\u00e7t\u00fcler.<\/span><\/p>\n Her hasta d\u00f6rt ilac\u0131n her birinde \u00f6l\u00e7\u00fcld\u00fc\u011f\u00fc i\u00e7in, ortalama reaksiyon s\u00fcresinin ila\u00e7lar aras\u0131nda farkl\u0131l\u0131k g\u00f6sterip g\u00f6stermedi\u011fini belirlemek i\u00e7in tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA’s\u0131n\u0131 kullanaca\u011f\u0131z.<\/span><\/p>\n Python’da tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA’y\u0131 ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki ad\u0131mlar\u0131 kullan\u0131n.<\/span><\/p>\n Ad\u0131m 1: Verileri girin.<\/strong><\/span><\/p>\n \u00d6ncelikle verilerimizi tutacak bir pandas DataFrame olu\u015fturaca\u011f\u0131z:<\/span><\/p>\n Ad\u0131m 2: Tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA’y\u0131 ger\u00e7ekle\u015ftirin.<\/strong><\/span><\/p>\n Daha sonra, statsmodels<\/strong> k\u00fct\u00fcphanesindeki AnovaRM() fonksiyonunu<\/a> kullanarak tekrarlanan ANOVA \u00f6l\u00e7\u00fcmlerini ger\u00e7ekle\u015ftirece\u011fiz:<\/span><\/p>\n Ad\u0131m 3: Sonu\u00e7lar\u0131 yorumlay\u0131n.<\/strong><\/span><\/p>\n Tekrarlanan \u00f6l\u00e7\u00fcm ANOVA’s\u0131 a\u015fa\u011f\u0131daki bo\u015f ve alternatif hipotezleri kullan\u0131r:<\/span><\/p>\n S\u0131f\u0131r hipotezi (H 0<\/sub> ):<\/strong> \u00b5 1<\/sub> = \u00b5 2<\/sub> = \u00b5 3<\/sub> (n\u00fcfus ortalamalar\u0131n\u0131n t\u00fcm\u00fc e\u015fittir)<\/span><\/p>\n Alternatif hipotez: (Ha):<\/strong> en az bir pop\u00fclasyon ortalamas\u0131 di\u011ferlerinden farkl\u0131d\u0131r<\/span><\/p>\n Bu \u00f6rnekte F testi istatisti\u011fi 24,7589’dur<\/strong> ve buna kar\u015f\u0131l\u0131k gelen p de\u011feri 0,0000’dir<\/strong> .<\/span><\/p>\n Bu p de\u011feri<\/a> 0,05’ten k\u00fc\u00e7\u00fck oldu\u011fundan s\u0131f\u0131r hipotezini reddediyoruz ve d\u00f6rt ila\u00e7 aras\u0131ndaki ortalama yan\u0131t s\u00fcrelerinde istatistiksel olarak anlaml\u0131 bir fark oldu\u011fu sonucuna var\u0131yoruz.<\/span><\/p>\n Ad\u0131m 4: Sonu\u00e7lar\u0131 rapor edin.<\/strong><\/span><\/p>\n Son olarak tekrarlanan \u00f6l\u00e7\u00fcmlerimizin sonu\u00e7lar\u0131n\u0131 ANOVA olarak raporlayaca\u011f\u0131z. \u0130\u015fte bunun nas\u0131l yap\u0131laca\u011f\u0131na dair bir \u00f6rnek:<\/span><\/p>\n D\u00f6rt farkl\u0131 ilac\u0131n tepki s\u00fcresi \u00fczerindeki etkisini incelemek i\u00e7in 5 ki\u015fiye tek y\u00f6nl\u00fc tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA uyguland\u0131.<\/span><\/p>\n Sonu\u00e7lar, kullan\u0131lan ila\u00e7 t\u00fcr\u00fcn\u00fcn yan\u0131t s\u00fcresinde istatistiksel olarak anlaml\u0131 farkl\u0131l\u0131klara yol a\u00e7t\u0131\u011f\u0131n\u0131 g\u00f6sterdi (F(3, 12) = 24,75887, p < 0,001).<\/span><\/p>\n<\/blockquote>\n A\u015fa\u011f\u0131daki e\u011fitimler, tekrarlanan \u00f6l\u00e7\u00fcm ANOVA’lar\u0131 hakk\u0131nda ek bilgi sa\u011flar:<\/span><\/p>\n Tek y\u00f6nl\u00fc ANOVA ve tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA: fark<\/a> Tekrarlanan \u00f6l\u00e7\u00fcmler ANOVA, her grupta ayn\u0131 deneklerin yer ald\u0131\u011f\u0131 \u00fc\u00e7 veya daha fazla grubun ortalamalar\u0131 aras\u0131nda istatistiksel olarak anlaml\u0131 bir fark olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in kullan\u0131l\u0131r. Bu e\u011fitimde Python’da tek y\u00f6nl\u00fc tekrarlanan \u00f6l\u00e7\u00fcm ANOVA’s\u0131n\u0131n nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r. \u00d6rnek: Python’da Tekrarlanan \u00d6l\u00e7\u00fcmler ANOVA Ara\u015ft\u0131rmac\u0131lar d\u00f6rt farkl\u0131 ilac\u0131n farkl\u0131 reaksiyon s\u00fcrelerine neden olup olmad\u0131\u011f\u0131n\u0131 bilmek istiyorlar. Bunu […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-856","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: Python’da Tekrarlanan \u00d6l\u00e7\u00fcmler ANOVA<\/strong><\/span><\/h2>\n
import<\/span> numpy as<\/span> np\nimport<\/span> pandas as<\/span> pd\n\n#createdata<\/span>\ndf = pd.DataFrame({'patient': np.repeat([1, 2, 3, 4, 5], 4),\n 'drug': np.tile([1, 2, 3, 4], 5),\n 'response': [30, 28, 16, 34,\n 14, 18, 10, 22,\n 24, 20, 18, 30,\n 38, 34, 20, 44, \n 26, 28, 14, 30]})\n\n#view first ten rows of data<\/span> \ndf.head[:10]\n\n\n\tpatient drug response\n0 1 1 30\n1 1 2 28\n2 1 3 16\n3 1 4 34\n4 2 1 14\n5 2 2 18\n6 2 3 10\n7 2 4 22\n8 3 1 24\n9 3 2 20<\/strong><\/pre>\n from<\/span> statsmodels.stats.anova import<\/span> AnovaRM\n<\/span>\n#perform the repeated measures ANOVA<\/span>\nprint(AnovaRM(data= df<\/span> , depvar=' response<\/span> ', subject=' patient<\/span> ', within=[' drug<\/span> ']).fit())\n\n Anova\n====================================\n F Value Num DF Den DF Pr > F\n----------------------------------\ndrug 24.7589 3.0000 12.0000 0.0000\n====================================\n<\/strong><\/pre>\n\n
Ek kaynaklar<\/strong><\/span><\/h2>\n
Tekrarlanan \u00d6l\u00e7\u00fcmlerin Manuel Olarak Ger\u00e7ekle\u015ftirilmesi ANOVA<\/a>
Tekrarlanan \u00f6l\u00e7\u00fcmlerin \u00fc\u00e7 varsay\u0131m\u0131 ANOVA<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"