From means and variances to persons and patterns

A novel approach for conceptualizing and analyzing data from psychological studies is presented and discussed. This approach is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. These models therefore go beyond the variable-...

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Published inFrontiers in psychology Vol. 6; p. 1007
Main Author Grice, James W
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 24.07.2015
Subjects
Inference to best explanation
integrated model
mean
Observation Oriented Modeling
Psychology
Variable-Based Modeling
observation oriented modeling
integrated model
inference to best explanation
variable-based modeling
mean
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Summary:A novel approach for conceptualizing and analyzing data from psychological studies is presented and discussed. This approach is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. These models therefore go beyond the variable-based, path models in use today which are limiting with regard to the types of inferences psychologists can draw from their research. In terms of analysis, the newer approach replaces traditional aggregate statistics such as means, variances, and covariances with methods of pattern detection and analysis. While these methods are person-centered and do not require parametric assumptions, they are both demanding and rigorous. They also provide psychologists with the information needed to draw the primary inference they often wish to make from their research; namely, the inference to best explanation.
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Edited by: Craig Speelman, Edith Cowan University, Australia
This article was submitted to Quantitative Psychology and Measurement, a section of the journal Frontiers in Psychology.
Reviewed by: David Trafimow, New Mexico State University, USA; Brian D. Haig, University of Canterbury, New Zealand
ISSN:1664-1078
1664-1078
DOI:10.3389/fpsyg.2015.01007