Multiple Deprivation, Severity and Latent Sub-Groups: Advantages of Factor Mixture Modelling for Analysing Material Deprivation
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DOI: 10.1007/s11205-016-1272-y
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- Francesco Dotto & Alessio Farcomeni & Maria Grazia Pittau & Roberto Zelli, 2019. "A dynamic inhomogeneous latent state model for measuring material deprivation," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(2), pages 495-516, February.
- Alessio Farcomeni & Monia Ranalli & Sara Viviani, 2021. "Dimension reduction for longitudinal multivariate data by optimizing class separation of projected latent Markov models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 462-480, June.
- Zenghui Huo & Mei Zhang & Junhui Han, 2022. "Heterogeneity of Capability Deprivation and Subjective Sense of Gain: Analysis of Factor Mixture Models Based on 892 Rural Households in Six Provinces," IJERPH, MDPI, vol. 19(7), pages 1-16, April.
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Keywords
Deprivation; Poverty; Severity; Latent class analysis; Factor mixture model;All these keywords.
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