Akademik Veri Yönetim Sistemi
12th International Conference of the International Biometric Society's Eastern Mediterranean Region, EMR2023, İzmir, Türkiye, 8 - 11 Mayıs 2023, ss.48
Mixed design analysis of variance in repeated measurements allows the examination of data obtained
from the same measurement performed multiple times. Bayesian and frequentist approaches are two
different methods used for estimating a parameter for repeated measurements. In this study, the results
obtained from bayesian and frequentist approaches for repeated measurements in balanced and
unbalanced samples were investigated. The aim of this study is to compare the results of both
frequentist and bayesian approaches using the mixed design ANOVA method for data obtained from
four repeated exponential distributions with different coefficient of variations and
balanced/unbalanced designs (4x4). Datasets with coefficient of variation of 0.5 and 1 were generated
from the exponential distribution for the study design, which consists of balanced and unbalanced
samples. The inclusion of unbalanced design aims to achieve positive heterogeneity by increasing the
variance. The simulation study was repeated 1000 times. Evaluations were made using both frequentist
and bayesian approaches, and the results were evaluated according to confidence intervals, and the
approaches were compared. Bayesian and frequentist approaches offer different methods for
estimating a parameter in repeated measurements. Both methods have advantages and disadvantages.
The choice of appropriate method may depend on the availability of prior information; Bayesian
approach may yield more accurate results if prior information is available, while frequentist approach
may be more appropriate if no prior information is available. In conclusion, both approaches can be
used as alternatives to each other in repeated measurements.