Fachgruppe für Methoden und Evaluation - Universität Bamberg
Fachgruppe für Methoden und Evaluation - Universität Bamberg
Fachgruppe für Methoden und Evaluation - Universität Bamberg
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Fr., 23.09., K eynote: Tenko<br />
(H)<br />
Raykov,<br />
11.30-12.30 Uhr, Hörsaal M3/232N<br />
On Missing Data Mechanisms and Analysis of Incomplete Data Sets in Behavioral,<br />
Social, and Biomedical Research<br />
Tenko Raykov<br />
Measurement &<br />
Quantitative Methods<br />
Michigan State<br />
University<br />
East Lansing, MI, USA<br />
Missing data pervade empirical research in psychology<br />
and the behavioral, social, and biomedical disciplines.<br />
This talk shows that contrary to statements and implications<br />
from a considerable body of widely circulated and cited<br />
literature, the missing data mechanism routinely referred to<br />
as missing completely at random (MCAR) is not testable<br />
via examination for distributional differences between<br />
groups with observed and with missing data. A discussion<br />
is provided, from a formal logic standpoint, of the distinction<br />
between necessary conditions and sufficient conditions.<br />
It is shown that lack of group distributional differences is<br />
not sufficient for MCAR, and it is argued that the importance<br />
of MCAR has been frequently overrated in empirical behavioral,<br />
social, and biomedical research. A multiple testing<br />
approach to examining an incomplete data set for not<br />
being MCAR is outlined. A latent variable method discussed<br />
in Raykov (2001, Structural Equation Modeling) is recommended<br />
when fitting models containing covariates with<br />
missing values using maximum likelihood in the presence<br />
of auxiliary variables.<br />
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