GJEIS
Global Journal of Enterprise Information System
Introduction to Simple Mediation Analysis in SPSS
Nitika Sharma
Nitika Sharma Assistant Professor of MAIT, Delhi, India
[email protected]
Data is analyzed using Mediation model which focuses on the
estimation of the indirect effect of X on Y through an intermediary mediator variable M causally located between X and Y (i.e.,
a model of the form X → M → Y )1, where X is the input variable,
Y is output and M is the Mediating Variable. When researchers
want to examine that how X variable exert it effects on Y variable
which is commonly intervened by one or two variables denoted
by M and this variable has a causal relationship between X & Y
as per Figure 1 and termed as Simple Mediation Model. In this
casual system there is at least one casual antecedent X variable
is projected as influencing an outcome Y through a single intervening variable M. Such model establishes two pathways which
influences Y by direct effect and indirect effect. In direct effect,
pathways lead from X to Y without passing M. In indirect effects,
a pathway of X to Y is lead through M. There are two consequent variables forming two equations and these equations can
be estimated by conducting OLS regression analyses using SPSS
or by using PROCESS.sps in SPSS by Andrew F. Hayes. To add
PROCESS by Andrew F. Hayes in SPSS following are the steps:1. Download the PROCESS.sps from www.afhayes.com and
save it on desktop.
2. Open SPSS as an administrator
3. Click on Utilities and select Custom Dialogues
Figure 1. A Simple Mediation Model with single Mediator variable M causally located between X & Y.
*Author for correspondence
Nitika Sharm
Vol 7 | Issue 1 | January-March 2015 | www.gjeis.org
Research Thought
GJEIS | Print ISSN: 0975-153X | Online ISSN: 0975-1432
63
Introduction to Simple Mediation Analysis in SPSS
4. In Custom Dialogue, click Install Custom Dialogue and
choose the file PROCESS.sps from desktop
5. From Analyze, in Regression you will find an option for
PROCESS by Andrew F Hayes
6. To compute the simple mediation model fill the Outcome
Variable (Y), Independent Variable (X) and Mediating
Variable (M)
7. There will be two consequent variables forming two equations
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Vol 7 | Issue 1 | January-March 2015 | www.gjeis.org
i. M= i1 + aX+ eM
ii. Y= i2 + c’X+ bM + eY
Reference
1. Hayes AF. Introduction to Mediation, Moderation, and Conditional
Process Analysis: A Regression-Based Approach. New York, NY:
The Guilford Press; 2013.
GJEIS | Print ISSN: 0975-153X | Online ISSN: 0975-1432