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Finding Optimal Age Groups for Investigating Age-Related Variables

Finding Optimal Age Groups for Investigating Age-Related Variables A problem in researching the effects of aging hasbeen the identification of ‘optimal’ age groups akin to developmental stages. This paper shows how factor analysis was used in connection with attitudinal data to segment the age range from15 to 64 years. The resulting five age groups were: 15–18, 19–26,27–39, 40–52, and 53–64 years. These age groups appear to be forming distinct attitudinal stages in the 15–64 age range. The relatively clean solution obtained here suggests experimentation with other analytical methods for cross-validation purposes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Human Development Karger

Finding Optimal Age Groups for Investigating Age-Related Variables

Human Development , Volume 16 (4): 11 – Jan 1, 2009

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Publisher
Karger
Copyright
© 1973 S. Karger AG, Basel
ISSN
0018-716X
eISSN
1423-0054
DOI
10.1159/000271283
Publisher site
See Article on Publisher Site

Abstract

A problem in researching the effects of aging hasbeen the identification of ‘optimal’ age groups akin to developmental stages. This paper shows how factor analysis was used in connection with attitudinal data to segment the age range from15 to 64 years. The resulting five age groups were: 15–18, 19–26,27–39, 40–52, and 53–64 years. These age groups appear to be forming distinct attitudinal stages in the 15–64 age range. The relatively clean solution obtained here suggests experimentation with other analytical methods for cross-validation purposes.

Journal

Human DevelopmentKarger

Published: Jan 1, 2009

Keywords: Aging; Attitudes; Q-analysis; Optimal age groups; Developmental stages; Factor analysis

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