The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Longitudinal Selectivity in Aging Populations: Separating Mortality-Associated Versus Experimental Components in the Berlin Aging Study (BASE)
Open accessAbstract
The authors examined 3.7-year selectivity in the Berlin Aging Study by comparing the T1 parent sample (N = 516) with the T3 sample (N = 206). Selectivity was partitioned into a mortality-associated component, reflecting the degree to which individuals still alive at T3 (T3 survivors, N = 313) differ from the T1 parent sample (N = 516) from which they originated, and an experimental component, reflecting the degree to which the T3 sample (N = 206) differed from T3 survivors (N = 313). Across 48 variables representing medical, sensorimotor, cognitive, personality-related, and socioeconomic domains, the mortality-associated component accounted for 64% of total selectivity, and the experimental component for 36% (0.18 vs 0.10 SD units; t = 7.20, p <.01). Except for age and intelligence, experimental selectivity effects regarding means and prevalence rates were generally small. Partitioning selectivity into mortality-associated and experimental components is a useful tool in the longitudinal study of aging populations.
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“Individuals who drop out from a longitudinal study often differ from those who stay on dimensions of interest-they tend to be less healthy, less cognitively fit, and less engaged in stimulating activities, thereby restricting the observable range of variation (e.g., Ghisletta, McArdle, & Lindenberger, 2006; Lindenberger, Singer, & Baltes, 2002) and potentially biasing estimates of the rel”
From Enrichment Effects on Adult Cognitive Development: Can the Functional Capacity of Older Adults Be Preserved and Enhanced? (2008) · cites this paper as Lindenberger, Singer, & Baltes, 2002
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Cites
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
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Everitt, B. S. (2001) · Psychology Press eBooks · doi:10.4324/9781410605542-11 · Cited by 6,877
Baltes, P. B., & Lindenberger, U. (1997) · Psychology and Aging · doi:10.1037/0882-7974.12.1.12 · Cited by 1,509
Self-citationAnalysis of Longitudinal Data.
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Life-span Developmental Psychology: Introduction To Research Methods
Baltes, P. B., Reese, H. W., & Nesselroade, J. R. (1977) · MPG.PuRe (Max Planck Society) · Cited by 696
Self-citationLittle, T. D., Lindenberger, U., & Nesselroade, J. R. (1999) · Psychological Methods · doi:10.1037/1082-989x.4.2.192 · Cited by 626
Self-citationThe Berlin Aging Study: Aging From 70 To 100.
Baltes, P. B., Mayer, K. U., & Hoffmann, R. A. (1999) · Care management journals · doi:10.1891/1521-0987.1.4.281 · Cited by 602
Self-citationLindenberger, U., & Baltes, P. B. (1997) · Psychology and Aging · doi:10.1037//0882-7974.12.3.410 · Cited by 542
Self-citation(1998) · Cambridge University Press eBooks · doi:10.1017/cbo9780511586545 · Cited by 542
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Regional Brain Changes in Aging Healthy Adults: General Trends, Individual Differences and Modifiers
Raz, N., Lindenberger, U., Rodrigue, K. M., Kennedy, K. M., Head, D., Williamson, A., Dahle, C., Gerstorf, D., & Acker, J. D. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhi044 · Cited by 2,875
“At the same time, longitudinal studies tend to underestimate population change because of non-random attrition and retest effects (Lindenberger et al., 2002).”
BackgroundSelf-citationHertzog, C., Kramer, A. F., Wilson, R. S., & Lindenberger, U. (2008) · Psychological Science in the Public Interest · doi:10.1111/j.1539-6053.2009.01034.x · Cited by 1,495
Self-citationVoelcker‐Rehage, C., Godde, B., & Staudinger, U. M. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00026 · Cited by 472
“Thus, we performed selectivity analyses comparing the sample characteristics at t1 with the sample used for data analyses (sample at t3) for age, education, IQ, health, activity index, BMI, hypertension, positive affect, and self-efficacy (Lindenberger et al., 2002).”
MethodHuman cognitive aging: Corriger la fortune?
Lindenberger, U. (2014) · Science · doi:10.1126/science.1254403 · Cited by 414
Self-citationKotter-Grühn, D., Kleinspehn-Ammerlahn, A., Gerstorf, D., & Smith, J. (2009) · Psychology and Aging · doi:10.1037/a0016510 · Cited by 347
Metadata
- Authors
- Lindenberger, U., Singer, T., & Baltes, P. B.
- Affiliations
- Max Planck Institute for Human Development (DE)
- Max Planck Society (DE)
- Corresponding author
- Lindenberger, U.
- Venue
- The Journals of Gerontology Series B: Psychological Sciences and Social Sciences
- Publisher
- Oxford University Press (OUP)
- Published
- 2002-11-01
- Volume
- 57
- Issue
- 6
- Pages
- P474-P482
- ISSN
- 1079-5014 (ISSN-L)
- 1758-5368
- OpenAlex
- W2140385093
- Cited by
- 147
- References
- 24
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 1 · 2023: 1 · 2022: 5 · 2021: 6 · 2020: 3 · 2019: 6 · 2018: 8 · 2017: 2 · 2016: 6 · 2015: 13 · 2014: 7 · 2013: 7 · 2012: 6
- FWCI
- 10.14
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journals of Gerontology Series B (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion, other-oa)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Universität des Saarlandes
- Max-Planck-Institut für Bildungsforschung
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Aging and Gerontology Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Aging, Health, and Disability
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- population aging, Berlin Aging Study, older adults, cognitive aging, personality, socioeconomic status, intelligence, prevalence rates, sample attrition
- MeSH terms
- Aged, Aged, 80 and over, Aging, Attitude, Female, Geriatrics, Health Status, Humans, Longitudinal Studies, Male, Mortality, Personal Satisfaction, Personality, Population Surveillance, Social Support, Socioeconomic Factors, Geriatric Assessment, Consensus
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