AU - Baghfalaki, T.
AU - Ganjali, M.
AU - Khounsiavash, M.
TI - A Non-Random Dropout Model for Analyzing Longitudinal Skew-Normal Response
PT - JOURNAL ARTICLE
TA - JIRSS
JN - JIRSS
VO - 11
VI - 2
IP - 2
4099 - http://jirss.irstat.ir/article-1-188-en.html
4100 - http://jirss.irstat.ir/article-1-188-en.pdf
SO - JIRSS 2
AB - 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.
CP - IRAN
IN -
LG - eng
PB - JIRSS
PG - 101
PT -
YR - 2012