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Composite Measures for Assessing Multidimensional Social Exclusion in Later Life: Conceptual and Methodological Challenges

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  • Sinéad Keogh

    (National University of Ireland Galway)

  • Stephen O’Neill

    (National University of Ireland Galway
    London School of Hygiene and Tropical Medicine)

  • Kieran Walsh

    (National University of Ireland Galway)

Abstract

Although there are a number of approaches to constructing a measure of multidimensional social exclusion in later life, theoretical and methodological challenges exist around the aggregation and weighting of constituent indicators. This is in addition to a reliance on secondary data sources that were not designed to collect information on social exclusion. In this paper, we address these challenges by comparing a range of existing and novel approaches to constructing a composite measure and assess their performance in explaining social exclusion in later life. We focus on three widely used approaches (sum-of-scores with an applied threshold; principal component analysis; normalisation with linear aggregation), and three novel supervised machine-learning based approaches (least absolute shrinkage and selection operator; classification and regression tree; random forest). Using an older age social exclusion conceptual framework, these approaches are applied empirically with data from Wave 1 of The Irish Longitudinal Study on Ageing (TILDA). The performances of the approaches are assessed using variables that are causally related to social exclusion.

Suggested Citation

  • Sinéad Keogh & Stephen O’Neill & Kieran Walsh, 2021. "Composite Measures for Assessing Multidimensional Social Exclusion in Later Life: Conceptual and Methodological Challenges," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(2), pages 389-410, June.
    • Handle: RePEc:spr:soinre:v:155:y:2021:i:2:d:10.1007_s11205-021-02617-7
    DOI: 10.1007/s11205-021-02617-7
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    2. Matheus Pereira Libório & Oseias da Silva Martinuci & Alexei Manso Correa Machado & Renata de Mello Lyrio & Patrícia Bernardes, 2022. "Time–Space Analysis of Multidimensional Phenomena: A Composite Indicator of Social Exclusion Through k-Means," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 159(2), pages 569-591, January.
    3. Thomas Hansen & Marcela Petrová Kafková & Ruth Katz & Ariela Lowenstein & Sigal Naim & George Pavlidis & Feliciano Villar & Kieran Walsh & Marja Aartsen, 2021. "Exclusion from Social Relations in Later Life: Micro- and Macro-Level Patterns and Correlations in a European Perspective," IJERPH, MDPI, vol. 18(23), pages 1-16, November.
    4. Jiménez-Fernández, Eduardo & Sánchez, Angeles & Ortega-Pérez, Mario, 2022. "Dealing with weighting scheme in composite indicators: An unsupervised distance-machine learning proposal for quantitative data," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).

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