A Non-Random Dropout Model for Analyzing Longitudinal Skew-Normal Response

In this paper, multivariate skew-normal distribution is em- ployed for analyzing an outcome based dropout model for repeated mea- surements with non-random dropout in skew regression data sets. a probit regression is considered as the conditional probability of an ob- servation to be missing given outcomes. a simulation study of using the proposed methodology and comparing it with a semi-parametric method, gee, is provided. the standardized bias is used for compari- son of different approaches. furthermore, for investigation of efficiency of the methodology two applications are analyzed where observed infor- mation matrix is used to find the variances of the parameter estimates. in one of the applications a sensitivity analysis is also performed to in- vestigate the change on the response model’s parameter estimates due to perturbation of drop-out model’s parameter of interest