Principal components Analysis and Factor Analysis 2010

Instructor: Jose Manuel Roche, OPHI Research Officer

Class Objectives:

  • Data reduction with Principal Component Analysis
  • Exploratory Factor Analysis, measurement error and scale construction
  • Hypothesis testing with Confirmatory Factor Analysis
  • Introduction to other related techniques: Multiple Correspondence Analysis, Cluster Analysis and Structure Equation Modeling
  • Reviewing the strengths and weaknesses

Videos

[flashvideo title=Poverty Orderings image=wp-content/uploads/default_video.jpg file=wp-content/uploads/summerschool-2010_14_9.m4v /]

Download Lecture Slides (pdf)

Principal components Analysis and Factor Analysis

Exercise Files (dta file)

Working Group 2 (Stata Dataset)

Reading List
Suggested basic readings on this topic:
BROWN, T. A. (2006) Confirmatory factor analysis for applied research, New York, NY ; London, New York, NY ; London : Guilford Press. (Chapter 2: The common Factor Model and Exploratory Factor Analysis)
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.
HAMILTON, L. C. (2009) Statistics with Stata : updated for version 10, Belmont, CA, Brooks/Cole. (Chapter 12: Principal Components, Factor, and Cluster Analysis)
HEATH, A. and J. MARTIN (1997) ‘Chapter 3: Why Are There so Few Formal Measuring Instruments in Social and Political Research?’ IN LYBERG, L. (Ed.) Survey measurement and process quality. New York ; Chichester, Wiley.
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.
TREIMAN, D. J., D. D. JOHNSTON and T. J. GRITES (2009) Quantitative data analysis : doing social research to test ideas, 1st ed., San Francisco, Calif., Jossey-Bass ; Chichester : John Wiley [distributor]. (Chapter 11 Scale Construction)

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.
BROWN, T. A. (2006) Confirmatory factor analysis for applied research, New York, NY ; London, New York, NY ; London : Guilford Press.
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.
EVERITT, B. (2001) Cluster analysis, London: New York, London: Arnold; New York: Oxford University Press.
GRIMM, L. G. and P. R. YARNOLD (2000) Reading and understanding more multivariate statistics, Washington, DC ; London, American Psychological Association. (Chapter 7 Structural Equation Modeling)
HARRINGTON, D. (2009) Confirmatory factor analysis, Oxford, Oxford University Press.
KLASEN, S. (2000) “Measuring Poverty and Deprivation in South Africa”. Review of Income and Wealth, 46, 33-58.
KLINE, R. B. (2005) Principles and practice of structural equation modeling, 2nd ed., New York ; London, Guilford. (Chapter 1-4)
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.
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.
LE ROUX, B. and H. ROUANET (2010) Multiple correspondence analysis, Los Angeles, Calif. ; London, Los Angeles, Calif. ; London : SAGE.
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 Resources:
Multivariate data analysis in STATA: http://www.stata.com/capabilities/mv.html
Annotated STATAOutput FA: http://www.ats.ucla.edu/stat/stata/output/fa_output.htm
Annotated SPSS Output FA: http://www.ats.ucla.edu/stat/spss/output/factor1.htm