Template-Type: ReDIF-Paper 1.0
Author-Name: Alfons, A.
Author-Name-Last: Alfons
Author-Name-First: Andreas
Author-Name: Ates, N.Y.
Author-Name-Last: Ates
Author-Name-First: Nufer
Author-Name: Groenen, P.J.F.
Author-Name-Last: Groenen
Author-Name-First: Patrick
Author-Person: pgr229
Title: A Robust Bootstrap Test for Mediation Analysis
Abstract: Mediation  analysis  is  central  to  theory  building  and  testing  in  organizations  research. Management scholars often use linear regression analysis based on normal-theory maximum likelihood  estimators  to  test  mediation.  However, these  estimators  are  very  sensitive  to deviations  from  normality assumptions,  such  as  outliers  or  heavy  tails of  the  observed distribution. This   sensitivity   seriously   threatens   the   empirical   testing   of   theory   about mediation  mechanisms,  as  many  empirical  studies lack reporting of outlier treatments and checks  on model  assumptions. To  overcome this threat,  we  develop  a  fast  and  robust mediation  method  that  yields  reliable  results  even  when  the  data deviate from normality assumptions.  Simulation  studies  show  that  our  method  is  both  superior  in  estimating  the effect  size  and  more  reliable  in  assessing  its  significance  than  the  existing  methods.  We illustrate  the  mechanics  of  our  proposed  method  in  three  empirical  cases  and provide freely available software in R and SPSS to enhance its accessibility and adoption by researchers and practitioners.
Length: 45
Creation-Date: 2018-08-03
File-URL: https://repub.eur.nl/pub/109594/ERS-2018-005-MKT.pdf
File-Format: application/pdf
Series: RePEc:ems:eureri
Number: ERS-2018-005-MKT
Keywords: Mediation analysis, robust statistics, linear regression, bootstrap
Handle: RePEc:ems:eureri:109594