Fachgruppe für Methoden und Evaluation - Universität Bamberg

Fr., 23.09., Mediationsanalysen, 16.10-16.30 Uhr, Hörsaal M3/232N (H)
Identification of mediator variables in randomized longitudinal trials
Holger Brandt
Andreas Klein
Abteilung für Psychologische
Methodenlehre
Evaluation und Forschungsmethodik
Goethe-
Universität Frankfurt
Mertonstr. 17
60054 Frankfurt
brandt@psy.uni-frankfurt.de
In intervention studies concerning treatment efficacy the interest
in mediator variables has been increasing. Mediator
variables are variables which act between an intervention
and an outcome variable and which are intended to capture
the effect of the intervention on the outcome. The knowledge
about mediator variables enhances the understanding
of the mechanisms transmitting the effect of the intervention.
Different approaches have been suggested in order
to identify potential mediator variables, which have in
common that they condition on the mediator variable in order
to quantify the mediated effect (e.g. Baron & Kenny,
1986; Prentice, 1989). However, serious concerns about
this type of methodology have been raised in the more recent
statistical literature.
In this paper, we explain in more detail what steps might be
taken to modify the conventional approach, and we propose
a method that helps to reduce the bias for the estimation
of the mediated effect, when the data structure meets
specific requirements. The differences between the conventional
and the proposed method are exemplified by a
small simulation study and an empirical example. The results
indicate that in real-world situations the conventional
mediator model mostly leads to a strongly biased estimation
of the mediated effect. In comparison, the proposed
method leads to a reduced bias.
Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator
variable distinction in social psychological research:
Conceptual, strategic, and statistical considerations. Journal of
Personality and Social Psychology, 51, 1173-1182.
Prentice, R. L. (1989). Surrogate endpoints in clinical trials:
Definition and operational criteria. Statistics in Medicine, 8,
431-440.
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