“Generative Mechanisms and Multivariate Statistical Analysis: Modeling Educational Opportunity Inequality with a Multi-Matrix Log-Linear Topological Model: Contributions and Limitations”

“Generative Mechanisms and Multivariate Statistical Analysis: Modeling Educational Opportunity... Among techniques for the quantitative analysis of categorical data, log-linear models at present occupy a central place in social statistics, their sophistication and complexity having rapidly evolved over the past three decades. The article examines a specific variant of this approach to modeling which consists of log-linear topological models. It starts from the debate which followed introduction of the latter at the end of the 1970s to offer a new evaluation of the heuristic and methodological utility of this technique in light of recent discussion more generally concerned with the quantitative variables-based approach. In this regard, the article puts forward two arguments. It first maintains that log-linear topological models, especially in their multi-matrix variant, are extremely useful in integrating sociological theory with empirical quantitative analysis. It then shows that the principal shortcoming of these models is that they only partially allow the accurate modeling of the generative mechanisms underlying all the empirical regularities observed in aggregate data. These models are thus very attractive in that they go beyond the descriptive level of numerous works in quantitative sociology, and yet they are incapable of yielding explanations founded on the notion of generative mechanisms. In order not to remain at the abstract level of epistemological reflection, the article will attempt to show the well-foundedness of this thesis by constructing a multi-matrix log-linear topological model for the analysis of a contingency table which cross-classifies social origin with the educational qualification. The model is then tested against French survey data. To the extent that this model attempts to express ideas drawn from a specific theoretical approach – that of ‘rational educational choice’ – the analysis can contribute to both the study and understanding of inequalities in educational opportunity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

“Generative Mechanisms and Multivariate Statistical Analysis: Modeling Educational Opportunity Inequality with a Multi-Matrix Log-Linear Topological Model: Contributions and Limitations”

Loading next page...
 
/lp/springer_journal/generative-mechanisms-and-multivariate-statistical-analysis-modeling-AOvFtRic04
Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2006 by Springer
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-005-3963-3
Publisher site
See Article on Publisher Site

Abstract

Among techniques for the quantitative analysis of categorical data, log-linear models at present occupy a central place in social statistics, their sophistication and complexity having rapidly evolved over the past three decades. The article examines a specific variant of this approach to modeling which consists of log-linear topological models. It starts from the debate which followed introduction of the latter at the end of the 1970s to offer a new evaluation of the heuristic and methodological utility of this technique in light of recent discussion more generally concerned with the quantitative variables-based approach. In this regard, the article puts forward two arguments. It first maintains that log-linear topological models, especially in their multi-matrix variant, are extremely useful in integrating sociological theory with empirical quantitative analysis. It then shows that the principal shortcoming of these models is that they only partially allow the accurate modeling of the generative mechanisms underlying all the empirical regularities observed in aggregate data. These models are thus very attractive in that they go beyond the descriptive level of numerous works in quantitative sociology, and yet they are incapable of yielding explanations founded on the notion of generative mechanisms. In order not to remain at the abstract level of epistemological reflection, the article will attempt to show the well-foundedness of this thesis by constructing a multi-matrix log-linear topological model for the analysis of a contingency table which cross-classifies social origin with the educational qualification. The model is then tested against French survey data. To the extent that this model attempts to express ideas drawn from a specific theoretical approach – that of ‘rational educational choice’ – the analysis can contribute to both the study and understanding of inequalities in educational opportunity.

Journal

Quality & QuantitySpringer Journals

Published: Oct 11, 2005

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off