The influence of mortality on twin models of change: Addressing missingness through multiple imputation

Nancy L. Pedersen, Samuli Ripatti, Stig Berg, Chandra Reynolds, Scott M. Hofer, Deborah Finkel, Margaret Gatz, Juni Palmgren

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

Twin analyses of phenotypes that are associated with mortality may provide biased heritability estimates if the models require that data from both members of a pair are available. This is particularly true when longitudinal analyses are applied to measures of cognition or biomarkers of aging. The effect of applying imputational techniques that include information on age at death was tested on longitudinal data from two twin studies of aging, each with up to four occasions of measurement. Measures of twin similarity for intercepts and slopes from three latent growth curve models were compared: without imputed data, including imputed data but without information on age at death, and including imputed data with information on age at death. Results indicated that twin similarity for slopes decreases when mortality is accounted for, but that considerable age-related covariation remains.

Original languageEnglish (US)
Pages (from-to)161-169
Number of pages9
JournalBehavior genetics
Volume33
Issue number2
DOIs
StatePublished - Mar 1 2003

Keywords

  • Digit symbol
  • Mortality
  • Multiple imputation

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Genetics(clinical)

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    Pedersen, N. L., Ripatti, S., Berg, S., Reynolds, C., Hofer, S. M., Finkel, D., Gatz, M., & Palmgren, J. (2003). The influence of mortality on twin models of change: Addressing missingness through multiple imputation. Behavior genetics, 33(2), 161-169. https://doi.org/10.1023/A:1022506018690