Multivariate Data Reduction Techniques

Instructor: José Manuel Roche, OPHI Researcher

Class Objectives:

  • Confirmatory Factor Analysis and multidimensional indices
  • Factor Analysis vs. Principal Component Analysis
  • Exploratory Factor Analysis and multidimensionality
  • Other techniques: Multiple Correspondence Analysis and Cluster Analysis
  • Strengths and weaknesses of multidimensional data reduction techniques

Multivariate Data Reduction Presentation


[flashvideo title=Multivariate Data Reduction image=wp-content/uploads/default_video.jpg file=wp-content/uploads/Multivariate-Data-Reduction-Techniques_JMR.m4v /]

Download Video (large file)
Multivariate Data Reduction Techniques
[To save file, right click to “Save Target As” (Windows) or control + click (Mac)]

Download Multivariate Data Exercises (zip file)

Reading List
Suggested basic readings on this topic:
CHIAPPERO-MARTINETTI, E. and J. M. ROCHE (2009) “Operationalization of the capability approach, from theory to practice: a review of techniques and empirical applications” in CHIAPPERO-MARTINETTI, E. (Ed.) Debating Global Society: Reach and Limits of the Capability Approach. Milan, Fondazione Feltrinelli.
HARRINGTON, D. (2009) Confirmatory factor analysis, Oxford, Oxford University Press.
KRISHNAKUMAR, J. and A. NAGAR (2007) ‘On Exact Statistical Properties of Multidimensional Indices Based on Principal Components, Factor Analysis, MIMIC and Structural Equation Models’. Social Indicators Research, 86 (3), 481-496.
ROCHE , J. M. (2008) ‘Monitoring Inequality among Social Groups: A Methodology Combining Fuzzy Set Theory and Principal Component Analysis’. Journal of Human Development and Capabilities, 9 (3), 427 – 452.

Further readings:
BALESTRINO, A. and N. SCICLONE (2000) “Should we use functioning instead of income to measure wellbeing?”. Rivista internazionale di scienze sociali, 53 (1), 3-22.
BERENGER, V. and A. VERDIER-CHOUCHANE (2007) “Multidimensional Measures of Well-Being: Standard of Living and Quality of Life Across Countries”. World Development, 35 (7), 1259-1276.
COSTELLO, A. and J. OSBORNE (2005) “Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis”. Practial Assessment, Research & Evaluation, 10 (7)
DI TOMMASO, M. L. (2007) ‘”Children capabilities: A structural equation model for India”. The Journal of Socio-Economics, 36, 436-450.
KLASEN, S. (2000) “Measuring Poverty and Deprivation in South Africa”. Review of Income and Wealth, 46, 33-58.
KRISHNAKUMAR, J. (2007) “Going Beyond Functioning to Capabilities: An Economic Model to Explain and Estimate Capabilities”. Journal of Human Development, 8 (1), 39-63.
KUKLYS, W. (2005) Amartya Sen’s Capability Approach: Theoretical Insights and Empirical Applications, Berlin, Springer.
LELLI, S. (2001) “Factor Analysis vs. Fuzzy Sets Theory: Assessing the Influence of Different Techniques on Sen’s Functioning Approach”. Centre of Economic Studies Discussion Paper, KU Leuven,
MCGILLIVRAY, M. (2005) “Measuring Non-economic Well-being Achievement”. Review of Income and Wealth, 51 (2), 337-364.
NEFF, D. F. (2007) “Subjective Well-Being, Poverty and Ethnicity in South Africa: Insights from an Exploratory Analysis”. Social Indicators Research, 80, 313-341.
SCHOKKAERT, E. and L. VAN OOTEGEM (1990) “Sen’s Concept of the Living Standard Applied to the Belgian Unemployment”. Research Economiques de Louvain, 56, 429-450.
VELICER, W. F. and D. N. JACKSON (1990) “Component Analysis Versus Common Factor-Analysis – Some Issues in Selecting an Appropriate Procedure”. Multivariate Behavioral Research, 25 (1), 1-28.
WIDAMAN, K. F. (1993) “Common Factor Analysis Versus Principal Component Analysis: Differential Bias in Representing Model Parameters?”. Multivariate Behavioral Research, 28 (3), 263.

Online sources:
Multivariate data analysis in STATA:
Annotated STATAOutput FA:
Annotated SPSS Output FA: