Constructing socio-economic status indices: how to use principal components analysis.
Seema Vyas,Lilani Kumaranayake +1 more
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How PCA-based indices are constructed, how they can be used, and their validity and limitations are reviewed, and issues related to choice of variables, data preparation and problems such as data clustering are addressed.Abstract:
Theoretically, measures of household wealth can be reflected by income, consumption or expenditure information. However, the collection of accurate income and consumption data requires extensive resources for household surveys. Given the increasingly routine application of principal components analysis (PCA) using asset data in creating socio-economic status (SES) indices, we review how PCA-based indices are constructed, how they can be used, and their validity and limitations. Specifically, issues related to choice of variables, data preparation and problems such as data clustering are addressed. Interpretation of results and methods of classifying households into SES groups are also discussed. PCA has been validated as a method to describe SES differentiation within a population. Issues related to the underlying data will affect PCA and this should be considered when generating and interpreting results.read more
Citations
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Socioeconomic status measurement with discrete proxy variables: is principal component analysis a reliable answer?
TL;DR: In this paper, the effects of discreteness of the observed variables on principal component analysis (PCA) are reviewed and the statistical properties of the popular Filmer and Pritchett (2001) procedure are analyzed.
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Measuring socio-economic position for epidemiological studies in low- and middle-income countries: a methods of measurement in epidemiology paper
Laura D Howe,Bruna Galobardes,Alicia Matijasevich,David Gordon,Deborah Johnston,Obinna Onwujekwe,Rita Patel,Elizabeth A Webb,Debbie A Lawlor,James R Hargreaves +9 more
TL;DR: This article describes the measures of SEP used in low- and middle-income countries (LMIC) in terms of its theoretical basis, interpretation, measurement, strengths and limitations, and provides brief comparisons between LMIC and HIC.
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Issues in the construction of wealth indices for the measurement of socio-economic position in low-income countries
TL;DR: The appropriateness of wealth indices as proxies for consumption expenditure is questioned, and the choice of data included had a greater influence on the wealth index than the method used to weight the data.
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Saverio Stranges,William W. Tigbe,Francesc Xavier Gómez-Olivé,Margaret Thorogood,Margaret Thorogood,Ngianga-Bakwin Kandala +5 more
TL;DR: This study corroborates the multifaceted nature of sleep problems, which is strongly linked to poorer general well-being and quality of life, and psychiatric comorbidities.
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Christina Pallitto,Claudia García-Moreno,Henrica A. F. M. Jansen,Lori Heise,Mary Ellsberg,Charlotte Watts +5 more
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References
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Estimating Wealth Effects without Expenditure Data or Tears: With an Application to Educational Enrollments in States of India
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