Year 2018, Volume 20 , Issue 1, Pages 1 - 6 2018-08-03

The Methods Used in Nonparametric Covariance Analysis
Parametrik Olmayan Kovaryans Analizinde Kullanılan Metotlar

Şengül CANGÜR [1] , Mehmet Ali SUNGUR [2] , Handan ANKARALI [3]


Aim: Nonparametric covariance analysis (ANCOVA) methods are used when the assumptions of parametric ANCOVA are not met and/or the dependent variable has bivariate/ordinal scale. In the nonparametric ANCOVA methodology, Quade, Puri & Sen and McSweeney & Porter methods are known as Ranked ANCOVA methods. However, commonly used programs do not have module(s) for applying these methods. The objective of this study is to introduce the ranked ANCOVA methods, to apply it in a web-based program developed by the authors and to present the advantages of these methods.

Material and Methods: The theoretical features and application steps of the Ranked ANCOVA methods are defined and a web-based program for the application of each method has been established. The application of each method on this program with the help of simulated data taken from the health field study, where the effect of cigarette smoking on biochemical tests was examined has also been included.

Results: Although there is no specific module in the widely used statistical programs for the methods described in this study, it is shown on a clinical study constituted with simulated data that these methods can easily be applied and the results of the methods are given.

Conclusion: The use of parametric methods for factorial models leads to an increase in Type-I error rate and a decrease in test power in many studies, where the sample size is limited and/or the dependent variable does not have normal distribution. To reduce this error, we recommend using the methods suggested in the study. These methods are also expected to reach widespread use thanks to the web-based program.

Amaç: Parametrik kovaryans analizi (ANCOVA) varsayımlarının sağlanamaması ve/veya bağımlı değişkenin iki değerli/sıralayıcı ölçekli olması durumunda, parametrik olmayan ANCOVA yaklaşımlarından yararlanılmaktadır. Parametrik olmayan ANCOVA metodolojisinde Quade, Puri & Sen ve McSweeney & Porter metotları, Ranklı ANCOVA yöntemleri olarak bilinmektedir. Ancak yaygın kullanılan programlarda, bu metotların uygulanmasına yönelik modül(ler) bulunmamaktadır. Bu çalışmanın amacı Ranklı ANCOVA yaklaşımlarını tanıtmak, yazarlar tarafından geliştirilen web tabanlı bir programda uygulamasını yapmak ve bu yaklaşımların avantajlarından bahsetmektedir.

Gereç ve Yöntemler: Ranklı ANCOVA yaklaşımlarının teorik özellikleri ve uygulama adımları tanımlanmış ve her bir yaklaşımın uygulanmasına yönelik web tabanlı bir program oluşturulmuştur. Sigara kullanma durumunun biyokimyasal tetkik sonuçları üzerindeki etkisinin incelendiği sağlık alanındaki bir çalışmadan simüle edilen veriler yardımıyla web tabanlı bir program üzerinde her bir yaklaşımın uygulamasına da yer verilmiştir.

Bulgular: Her ne kadar, bu çalışmada açıklanan yaklaşımlar için yaygın kullanılan istatistik programlarında özel bir modül olmasa da, bu yaklaşımların kolaylıkla uygulanabileceği simüle verilerle oluşturulmuş klinik bir çalışma üzerinde gösterilmiş, yaklaşımların sonuçları verilmiştir.

Sonuç: Birçok araştırmada örneklem genişliğinin kısıtlı olması ve/veya bağımlı değişkenin normal dağılım göstermemesi durumunda, faktöriyel modeller için parametrik yöntemlerin kullanılması, Tip I hata oranının artmasına ve testin gücünün azalmasına neden olmaktadır. Bu hatayı azaltmak için çalışmada önerilen yaklaşımların kullanılması tavsiye edilmektedir. Bu yaklaşımların, web tabanlı program sayesinde de yaygın kullanıma ulaşacağı düşünülmektedir.

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Primary Language en
Subjects Health Care Sciences and Services
Journal Section Research Article
Authors

Author: Şengül CANGÜR (Primary Author)
Institution: DÜZCE ÜNİVERSİTESİ, TIP FAKÜLTESİ
Country: Turkey


Author: Mehmet Ali SUNGUR
Institution: DÜZCE ÜNİVERSİTESİ, TIP FAKÜLTESİ
Country: Turkey


Author: Handan ANKARALI
Institution: İSTANBUL MEDENİYET ÜNİVERSİTESİ, TIP FAKÜLTESİ
Country: Turkey


Dates

Publication Date : August 3, 2018

Bibtex @research article { dtfd424774, journal = {Duzce Medical Journal}, issn = {}, eissn = {1307-671X}, address = {}, publisher = {Duzce University}, year = {2018}, volume = {20}, pages = {1 - 6}, doi = {10.18678/dtfd.424774}, title = {The Methods Used in Nonparametric Covariance Analysis}, key = {cite}, author = {CANGÜR, Şengül and SUNGUR, Mehmet Ali and ANKARALI, Handan} }
APA CANGÜR, Ş , SUNGUR, M , ANKARALI, H . (2018). The Methods Used in Nonparametric Covariance Analysis. Duzce Medical Journal , 20 (1) , 1-6 . DOI: 10.18678/dtfd.424774
MLA CANGÜR, Ş , SUNGUR, M , ANKARALI, H . "The Methods Used in Nonparametric Covariance Analysis". Duzce Medical Journal 20 (2018 ): 1-6 <https://dergipark.org.tr/en/pub/dtfd/issue/38727/424774>
Chicago CANGÜR, Ş , SUNGUR, M , ANKARALI, H . "The Methods Used in Nonparametric Covariance Analysis". Duzce Medical Journal 20 (2018 ): 1-6
RIS TY - JOUR T1 - The Methods Used in Nonparametric Covariance Analysis AU - Şengül CANGÜR , Mehmet Ali SUNGUR , Handan ANKARALI Y1 - 2018 PY - 2018 N1 - doi: 10.18678/dtfd.424774 DO - 10.18678/dtfd.424774 T2 - Duzce Medical Journal JF - Journal JO - JOR SP - 1 EP - 6 VL - 20 IS - 1 SN - -1307-671X M3 - doi: 10.18678/dtfd.424774 UR - https://doi.org/10.18678/dtfd.424774 Y2 - 2018 ER -
EndNote %0 Düzce Tıp Fakültesi Dergisi The Methods Used in Nonparametric Covariance Analysis %A Şengül CANGÜR , Mehmet Ali SUNGUR , Handan ANKARALI %T The Methods Used in Nonparametric Covariance Analysis %D 2018 %J Duzce Medical Journal %P -1307-671X %V 20 %N 1 %R doi: 10.18678/dtfd.424774 %U 10.18678/dtfd.424774
ISNAD CANGÜR, Şengül , SUNGUR, Mehmet Ali , ANKARALI, Handan . "The Methods Used in Nonparametric Covariance Analysis". Duzce Medical Journal 20 / 1 (August 2018): 1-6 . https://doi.org/10.18678/dtfd.424774
AMA CANGÜR Ş , SUNGUR M , ANKARALI H . The Methods Used in Nonparametric Covariance Analysis. Duzce Medical Journal. 2018; 20(1): 1-6.
Vancouver CANGÜR Ş , SUNGUR M , ANKARALI H . The Methods Used in Nonparametric Covariance Analysis. Duzce Medical Journal. 2018; 20(1): 6-1.