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The potential of model-based recursive partitioning in the social sciences – Revisiting Ockham's Razor
- Source :
- Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences ISBN: 9780203403020
- Publication Year :
- 2014
-
Abstract
- A variety of new statistical methods from the field of machine learning have the potential to offer new impulses for research in the social, educational and behavioral sciences. In this article we focus on one of these methods: model-based recursive partitioning. This algorithmic approach is reviewed and illustrated by means of instructive examples and an application to the Mincer equation. For readers unfamiliar with algorithmic methods, the explanation starts with the introduction of the predecessor method classification and regression trees. With respect to the application and interpretation of model-based recursive partitioning, we address the principle of parsimony and illustrate that the model-based recursive partitioning approach can be employed to test whether a postulated model is in accordance with Ockham's Razor or whether relevant covariates have been omitted. Finally, an overview of available statistical software is provided to facilitate the applicability in social science research.
- Subjects :
- Interpretation (logic)
Computer science
business.industry
10093 Institute of Psychology
Behavioural sciences
Recursive partitioning
Regression
Occam's razor
Field (computer science)
Variety (cybernetics)
Focus (linguistics)
symbols.namesake
symbols
Artificial intelligence
business
model-based recursive partitioning, structural change, parsimony, classification and regression trees (CART), algorithmic methods, data analysis
150 Psychology
Subjects
Details
- Language :
- English
- ISBN :
- 978-0-203-40302-0
- ISBNs :
- 9780203403020
- Database :
- OpenAIRE
- Journal :
- Contemporary Issues in Exploratory Data Mining in the Behavioral Sciences ISBN: 9780203403020
- Accession number :
- edsair.doi.dedup.....3e5f64027f394264353506b4beca451b