Determination of model fitting with power-divergence-type measure of departure from symmetry for sparse and non-sparse square contingency tables

Altun G., SARAÇBAŞI T.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, cilt.51, sa.7, ss.4087-4111, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 51 Sayı: 7
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/03610918.2020.1736301
  • Dergi Adı: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Applied Science & Technology Source, Business Source Elite, Business Source Premier, CAB Abstracts, Compendex, Computer & Applied Sciences, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.4087-4111
  • Anahtar Kelimeler: Measure of departure, Power-divergence family, Square contingency tables, Symmetry model, STATISTICS
  • Hacettepe Üniversitesi Adresli: Hayır

Özet

In this study, we propose a gradation to decide the model fitting under the symmetry model by using the departure measure. An extensive simulation study under different parameter settings and scenarios is conducted to introduce a gradation on unit interval. The proposed gradation provides an opportunity to decide the model fitting under the symmetry model when the chi-squared assumption does not hold for small sample sizes. The usefulness of proposed gradation is proved empirically using four applications to real data sets.