View Article |
Outlier detection in 2 × 2 crossover design using bayesian framework
Lim, F.P1, Mohamed, I.B2, Mohamed , N.A. @ A. Rahman3, Goh, S.L4.
We consider the problem of outlier detection method in 2×2 crossover design via Bayesian framework. We study the problem of outlier detection in bivariate data fitted using generalized linear model in Bayesian framework used by Nawama. We adapt their work into a 2×2 crossover design. In Bayesian framework, we assume that the random subject effect and the errors to be generated from normal distributions. However, the outlying subjects come from normal distribution with different variance. Due to the complexity of the resulting joint posterior distribution, we obtain the information on the posterior distribution from samples by using Markov Chain Monte Carlo sampling. We use two real data sets to illustrate the implementation of the method.
Affiliation:
- University of Malaya, Malaysia
- University of Malaya, Malaysia
- University of Malaya, Malaysia
- University of Malaya Medical Centre, Malaysia
Toggle translation
|
|
Indexation |
Indexed by |
MyJurnal (2021) |
H-Index
|
6 |
Immediacy Index
|
0.000 |
Rank |
0 |
Indexed by |
Web of Science (SCIE - Science Citation Index Expanded) |
Impact Factor
|
JCR (1.009) |
Rank |
Q4 (Multidisciplinary Sciences) |
Additional Information |
JCI (0.15) |
Indexed by |
Scopus 2020 |
Impact Factor
|
CiteScore (1.4) |
Rank |
Q2 (Multidisciplinary) |
Additional Information |
SJR (0.251) |
|
|
|