TY - JOUR
JF - JIRSS
JO - JIRSS
VL - 11
IS - 2
PY - 2012
Y1 - 2012/11/01
TI - A Non-Random Dropout Model for Analyzing Longitudinal Skew-Normal Response
TT - یک مدل انصراف غیر تصادفی برای تحلیل پاسخ چوله-نرمال طولی
N2 - 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.
SP - 101
EP - 129
AU - Baghfalaki, T.
AU - Ganjali, M.
AU - Khounsiavash, M.
AD -
KW - Dropout
KW - generalized estimating equations (GEE)
KW - longitu- dinal data
KW - observed information matrix
KW - selection model
KW - Skew-Normal distribution.
UR - http://jirss.irstat.ir/article-1-188-en.html
ER -