Science and Education Publishing American Journal of Applied Mathematics and Statistics 2328-7292 4 3 2016 7 2 Performance of Log-Beta Log-Logistic Regression Model 74 86 EN Mahmoud Riad Mahmoud Naglaa A. Morad Moshera A. M. Ahmad Department of Applied Statistics and Econometrics, Institute of Statistical Studies and Research, Cairo University AJAMS2016433 10.12691/ajams-4-3-3 2016 3 17 2016 5 1 2016 6 30 For the log-beta log-logistic regression model, we derive the appropriate matrices for assessing the local influence on the parameter estimates under perturbation scheme. Using a set of real data, global and local influences of individual observations on the stated model are considered. Besides, for different parameter settings, sample sizes, and censoring percentages, various simulation studies are performed to the performance of the log-beta log-logistic regression model. In addition, the empirical distribution of the martingale residuals is displayed against the normal distribution for comparison. These studies suggest that the martingale residual has shaped normal form.