TY - JOUR
T1 - Equivalence of two least-squares estimators for indirect effects
AU - Wang, Wen Wu
AU - Yu, Ping
AU - Zhou, Yuejin
AU - Tong, Tiejun
AU - Liu, Zhonghua
N1 - Funding Information:
Wang’s work is supported by National Natural Science Foundation of China (No.12071248), and National Statistical Science Research Project of China (No.2020LZ26).
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023/3
Y1 - 2023/3
N2 - In social and behavioral sciences, the mediation test based on the indirect effect is an important topic. There are many methods to assess intervening variable effects. In this paper, we focus on the difference method and the product method in mediation models. Firstly, we analyze the regression functions in the simple mediation model, and provide an expectation-consistent condition. We further show that the difference estimator and the product estimator are numerically equivalent based on the least-squares regression regardless of the error distribution. Secondly, we generalize the equivalence result to the three-path model and the multiple mediators model, and prove a general equivalence result in a class of restricted linear mediation models. Thirdly, we investigate the empirical distributions of the indirect effect estimators in the simple mediation model by simulations, and show that the indirect effect estimators are normally distributed as long as one multiplicand of the product estimator is large. Finally, we introduce some popular R packages for mediation analysis and also provide some useful suggestions on how to correctly conduct mediation analysis.
AB - In social and behavioral sciences, the mediation test based on the indirect effect is an important topic. There are many methods to assess intervening variable effects. In this paper, we focus on the difference method and the product method in mediation models. Firstly, we analyze the regression functions in the simple mediation model, and provide an expectation-consistent condition. We further show that the difference estimator and the product estimator are numerically equivalent based on the least-squares regression regardless of the error distribution. Secondly, we generalize the equivalence result to the three-path model and the multiple mediators model, and prove a general equivalence result in a class of restricted linear mediation models. Thirdly, we investigate the empirical distributions of the indirect effect estimators in the simple mediation model by simulations, and show that the indirect effect estimators are normally distributed as long as one multiplicand of the product estimator is large. Finally, we introduce some popular R packages for mediation analysis and also provide some useful suggestions on how to correctly conduct mediation analysis.
KW - Bootstrap
KW - Difference in coefficients
KW - Indirect effects
KW - Least-squares regression
KW - Mediation analysis
KW - Product of coefficients
UR - http://www.scopus.com/inward/record.url?scp=85109960081&partnerID=8YFLogxK
U2 - 10.1007/s12144-021-02034-6
DO - 10.1007/s12144-021-02034-6
M3 - Journal article
AN - SCOPUS:85109960081
SN - 1046-1310
VL - 42
SP - 7364
EP - 7375
JO - Current Psychology
JF - Current Psychology
IS - 9
ER -