TY - JOUR
T1 - Modified profile likelihood estimation for the Weibull regression models in survival analysis
AU - Islam, Md Mazharul
AU - Khan, Md Hasinur Rahaman
AU - Hawlader, Tamanna
N1 - Publisher Copyright:
© 2018, © 2018 Taylor & Francis Group, LLC.
PY - 2019/5/3
Y1 - 2019/5/3
N2 - In this study, adjustment of profile likelihood function of parameter of interest in presence of many nuisance parameters is investigated for survival regression models. Our objective is to extend the Barndorff–Nielsen’s technique to Weibull regression models for estimation of shape parameter in presence of many nuisance and regression parameters. We conducted Monte-Carlo simulation studies and a real data analysis, all of which demonstrate and suggest that the modified profile likelihood estimators outperform the profile likelihood estimators in terms of three comparison criterion: mean squared errors, bias and standard errors.
AB - In this study, adjustment of profile likelihood function of parameter of interest in presence of many nuisance parameters is investigated for survival regression models. Our objective is to extend the Barndorff–Nielsen’s technique to Weibull regression models for estimation of shape parameter in presence of many nuisance and regression parameters. We conducted Monte-Carlo simulation studies and a real data analysis, all of which demonstrate and suggest that the modified profile likelihood estimators outperform the profile likelihood estimators in terms of three comparison criterion: mean squared errors, bias and standard errors.
KW - Modified profile likelihood
KW - profile likelihood
KW - weibull regression model
UR - http://www.scopus.com/inward/record.url?scp=85055684944&partnerID=8YFLogxK
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U2 - 10.1080/03610926.2018.1472784
DO - 10.1080/03610926.2018.1472784
M3 - Article
AN - SCOPUS:85055684944
SN - 0361-0926
VL - 48
SP - 2329
EP - 2343
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 9
ER -