An ECM Estimation Approach for Analyzing Multivariate Skew-Normal Data with Dropout

Abstract

In this article, an ECM algorithm is developed to obtain the maximum likelihood estimates of parameters where multivariate skew-normal distribution is used for analyzing longitudinal skewed normal regression data with dropout. A simulation study is performed to investigate the performance of the presented algorithm. Also, the methodology is illustrated through two applications and the results of proposed methodology are compared with ECM under multivariate normal assumption using AIC and BIC criteria. Standard errors of parameter estimates are obtained by asymptotic observed information matrix.

Keywords:

• Dropout
• ECM algorithm
• EM algorithm
• Longitudinal data
• Skew-normal distribution

2000 Mathematics Subject Classification:

• 62H12
• 62P10

Acknowledgment

We are grateful to the Shahid Beheshti University for providing support.