Comparative Study of Generalized Estimating Equations and Logistic Regressions on Different Sample Sizes and Correlation Levels

Önder H.

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, vol.45, no.10, pp.3528-3533, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 45 Issue: 10
  • Publication Date: 2016
  • Doi Number: 10.1080/03610918.2015.1010000
  • Journal Name: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.3528-3533
  • Keywords: Autocorrelation, Generalized estimating equations, Logistic regressions, 62G05, 62G08, LONGITUDINAL DATA-ANALYSIS, POWER, GEE
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

In this study, it was aimed to determine accuracy of generalized estimating equations versus logistic regressions on different correlation levels and sample sizes. For this aim, two methods were compared with different sample sizes 10, 25, 50 and 100 and correlation levels 0.0, 0.3, 0.5 and 0.8. Result of this study showed that using generalized estimating equations could be preferred versus logistic regression when the sample size is over than 25 and correlation level is higher than 0.3 on data taken from studies with repeated measurements, but logistic regression could be better when the autocorrelations do not exist.