Exploring social mobility with latent trajectory groups
Exploring social mobility with latent trajectory groups
We present a new methodological approach to the study of social mobility. We use a latent class growth analysis framework to identify five qualitatively distinct social class trajectory groups between 1980 and 2000 for male respondents to the 1970 British Cohort Study. We model the antecedents of trajectory group membership via multinomial logistic regression. Non-response, which is a considerable problem in long-term panels and cohort studies, is handled via direct maximum likelihood estimation, which is consistent and efficient when data are missing at random. Our results suggest a combination of meritocratic and ascriptive influences on the probability of membership in the different trajectory groups.
65-88
Sturgis, Patrick
b9f6b40c-50d2-4117-805a-577b501d0b3c
Sullivan, Louise
c6cc3ed1-dff0-4924-a190-c7a2c4e081d4
2008
Sturgis, Patrick
b9f6b40c-50d2-4117-805a-577b501d0b3c
Sullivan, Louise
c6cc3ed1-dff0-4924-a190-c7a2c4e081d4
Sturgis, Patrick and Sullivan, Louise
(2008)
Exploring social mobility with latent trajectory groups.
Journal of the Royal Statistical Society: Series A (Statistics in Society), 171 (1), .
(doi:10.1111/j.1467-985X.2007.00516.x).
Abstract
We present a new methodological approach to the study of social mobility. We use a latent class growth analysis framework to identify five qualitatively distinct social class trajectory groups between 1980 and 2000 for male respondents to the 1970 British Cohort Study. We model the antecedents of trajectory group membership via multinomial logistic regression. Non-response, which is a considerable problem in long-term panels and cohort studies, is handled via direct maximum likelihood estimation, which is consistent and efficient when data are missing at random. Our results suggest a combination of meritocratic and ascriptive influences on the probability of membership in the different trajectory groups.
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Published date: 2008
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Local EPrints ID: 64621
URI: http://eprints.soton.ac.uk/id/eprint/64621
ISSN: 0964-1998
PURE UUID: 9d0373c0-2f77-43aa-8a69-6e383fee5fa0
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Date deposited: 13 Jan 2009
Last modified: 15 Mar 2024 12:01
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Author:
Patrick Sturgis
Author:
Louise Sullivan
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