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PERMÜTASYON TESTLERİNİN DOĞRUSAL MODELLERDE UYGULANMASI VE KARŞILAŞTIRILMASI

USE AND COMPARISON OF PERMUTATION TESTS IN LINEAR MODELS

Journal Name:

  • Anadolu Tarım Bilimleri Dergisi

Publication Year:

  • 2009

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
F and t-test are generally used to test significance of hypothesis and/or model parameters. Although parametric tests are considerably effective, they can be ineffective when the assumptions needed by model are not provided, which is a usual situation for many data sets. In this case, permutation test not affected by the assumptions can be applied as a non-parametric method. In this study, permutation tests such as permutation of raw data, permutation of residuals under full model and permutation of residuals under restricted model are compared for multiple linear regression, completely randomized designs, randomized block design and Latin square design in terms of the Type I error rates, and performance of each tests are studied via animal science data. Results from this study indicate that permutation tests yields more reliable results than parametric tests in terms of Type I error rate, and permutation tests are recommended in order to reduce Type I errors.
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Abstract (Original Language): 
Genellikle hipotezin ve/veya model parametrelerinin testi için F ve t-testleri kullanılır. Parametrik testler parametrik olmayan karşıtlarına göre daha etkili olsa da, pek çok veri seti için gerekli olan model varsayımlarının sağlanamadığı durumlarda, etkilerini yitirmektedirler. Bu durumda, varsayımlardan etkilenmeyen Permütasyon testleri parametrik olmayan bir yöntem olarak uygulanabilmektedir. Bu çalışmada, ham verinin permütasyonu, kalıntıların tam permütasyonu, kalıntıların kısmi permütasyonu yöntemleri, çoklu doğrusal regresyon, tesadüf parselleri, tesadüf blokları ve Latin kare deneme desenleri için I. tip hata olasılıkları bakımından karşılaştırılmıştır. Yöntemlerin karşılaştırılmasında hayvancılık verileri kullanılmıştır. Sonuç olarak, I Tip hata olasılığı bakımından Permütasyon testlerinin parametrik yöntemlere göre daha güvenilir sonuçlar ürettiği ve daha yüksek I. Tip hatadan kaçınmak için önerilebilecekleri görülmüştür.
FULL TEXT (PDF): 
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  • 2
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  • Turkish

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