The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON MATHEMATICS
Transactions ID Number: 89-645
Full Name: Anwar Fitrianto
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: Deapartment of Mathematics, Faculty of Science, University Putra Malaysia, 43400 UPM Serdang, Selangor
Country: MALAYSIA
Tel: +60162375915
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E-mail address: anwarfitrianto@gmail.com
Other E-mails: habshahmidi@gmail.com
Title of the Paper: Estimating Bias and RMSE of Indirect Effects using Rescaled Residual Bootstrap in Mediation Analysis
Authors as they appear in the Paper: Anwar Fitrianto, Habshah Midi
Email addresses of all the authors: anwarfitrianto@gmail.com,habshahmidi@gmail.com
Number of paper pages: 10
Abstract: It is a common practice to estimate the parameters of mediation model by using the Ordinary Least Squares (OLS) method. The construction of T statistics and confidence interval estimates for making inferences on the parameters of a mediation model, particularly the indirect effect, is usually are based on the assumption that the estimates are normally distributed. Nonetheless, in practice many estimates are not normal and have a heavy tailed distribution which may be the results of having outliers in the data. An alternative approach is to use bootstrap method which does not rely on the normality assumption. In this paper, we proposed a new bootstrap procedure of indirect effect in mediation model which is resistant to outliers. The proposed approach was based on residual bootstrap which incorporated rescaled studentized residuals, namely the Rescaled Studentized Residual Bootstrap using Least Squares (ReSRB). The Monte Carlo simulations showed that the!
ReSRB is more efficient than some existing methods in the presence of outliers.
Keywords: Mediation analysis, Outliers, Bootstrap, Studentized residuals, Indirect effect
EXTENSION of the file: .doc
Special (Invited) Session: Robust Bootstrap Approach to Estimate Bias and RMSE of Indirect Effects in Mediation Analysis
Organizer of the Session: 642-429
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