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Title: Analysis of Data from Related Individuals
Resulting in 1 citation.
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Baydar, Nazli Greek, April A. |
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Analysis of Data from Related Individuals Working Paper, Battelle Centers for Public Health Research and Evaluation, Seattle, WA, 2001 Cohort(s): Children of the NLSY79 Publisher: Battelle Human Affairs Research Center Keyword(s): Behavior Problems Index (BPI); Genetics; Kinship; Modeling; Peabody Individual Achievement Test (PIAT- Reading) This study extends the basic genetic factor models designed for twin data to examine data coming from children who belong to kinship groups of varying size and structure. To the extent that the genetic factor models could be extended to samples that are non-selective or less-selective than twin samples, more accurate estimates of genetic and environmental contributions may be obtained. In handling of data from kinship groups of children, several methodological and substantive issues arise. In order to demonstrate the implications of different approaches to resolve these issues, the estimates of ten models were compared that differed due to sample and model specification. The data come from children age 6-12 years in the 1992 National Longitudinal Survey of Youth-Children (NLSY-C). Analyses of the Peabody Individual Achievement Test (PIAT) for Reading Recognition and Behavior Problems Index (BPI) were conducted to estimate additive genetic and environmental components of variance. Results showed that estimates obtained from different methods of analysis varied substantially but were more robust for the PIAT scores than for the BPI scores. It was concluded that covariance structure models for kinship groups would make more efficient use of data from multiple related children than models for pairs of related children. |
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Bibliography Citation
Baydar, Nazli and April A. Greek. "Analysis of Data from Related Individuals." Working Paper, Battelle Centers for Public Health Research and Evaluation, Seattle, WA, 2001. |