Abstract
Biometric latent growth curve models were applied to data from the LTS in order to replicate and extend Wilson’s (Child Dev 54:298–316, 1983) findings. Assessments of cognitive development were available from 8 measurement occasions covering the period 4–15 years for 1032 individuals. Latent growth curve models were fit to percent correct for 7 subscales: information, similarities, arithmetic, vocabulary, comprehension, picture completion, and block design. Models were fit separately to WPPSI (ages 4–6 years) and WISC-R (ages 7–15). Results indicated the expected increases in heritability in younger childhood, and plateaus in heritability as children reached age 10 years. Heritability of change, per se (slope estimates), varied dramatically across domains. Significant genetic influences on slope parameters that were independent of initial levels of performance were found for only information and picture completion subscales. Thus evidence for both genetic continuity and genetic innovation in the development of cognitive abilities in childhood were found.
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References
Bartels M, Rietveld MJH, Van Baal GCM, Boomsma DI (2002) Genetic and environmental influences on the development of intelligence. Behav Genet 32(4):237–249
Bishop EG, Cherny SS, Corley RP, Plomin R, DeFries JC, Hewitt JK (2003) Developmental genetic analysis of general cognitive ability from 1 to 12 years in a sample of adoptees, biological siblings, and twins. Intelligence 31(1):31–49
Cardon LR, Fulker DW, DeFries JC, Plomin R (1992) Continuity and change in general cognitive ability from 1 to 7 years of age. Dev Psychol 28:1–10
Casto SD, DeFries JC, Fulker DW (1995) Multivariate genetic analysis of Wechsler Intelligence Scale for Children Revised (WISC-R) factors. Behav Genet 25(1):25–32
Chavarría-Siles I, Guillén F, Posthuma D (2014) Brain imaging and cognition. In: Finkel D, Reynolds CA (eds) Behavior genetics of cognition across the lifespan. Springer, New York, pp 235–256
Cherny SS, Fulker DW, Emde RN, Robinson J, Corley RP, Reznick JS, DeFries JC (1994) A developmental-genetic analysis of continuity and change in Bayley mental development index from 14 to 24 months: the MacArthur Longitudinal Twin Study. Psychol Sci 5(6):354–360
Dominicus A, Ripatti S, Pedersen NL, Palmgren J (2008) A random change point model for assessing variability in repeated mea- sures of cognitive function. Stat Med 27:5786–5798
Duncan OD (1961) Occupations and social status. Free Press, New York
Eaves LJ, Long J, Heath AC (1986) A theory of developmental change in quantitative phenotypes applied to cognitive development. Behav Genet 16(1):143–162
Finkel D, Davis DW (2009) Applying latent growth curve analysis to developmental synchronies in Louisville Twin Study data [Abstract]. Behav Genet 39:651
Finkel D, Reynolds CA (2009) Behavioral genetic investigations of cognitive aging. In: Kim Y-K (ed) Handbook of behavior genetics. Springer, New York, pp 101–112
Fulker DW, Cherny SS, Cardon LR (1993) Continuity and change in cognitive development. In: Plomin R, McClearn GE (eds) Nature, nurture and psychology. American Psychological Association, Washington, D.C., pp 77–97
Garrett HE (1946) A developmental theory of intelligence. Am Psychol 1:9
Ghisletta P, McArdle JJ (2012) Latent curve models and latent change score models estimated in R. Struct Equ Model 19:651–682
LaBuda MC, DeFries JC, Fulker DW (1987) Genetic and environmental covariance structures among WlSC-R subtests: a twin study. Intelligence 11:233–244
Logan JAR, Hart SA, Cutting L, Deater-Deckard K, Schatschneider C, Petrill S (2013) Reading development in young children: genetic and environmental influences. Child Dev 84(6):2131–2144
Lonigan CJ, Farver JM, Nakamoto J, Eppe S (2013) Developmental trajectories of preschool early literacy skills: a comparison of language-minority and monolingual-English children. Dev Psychol 49(10):1943–1957
Luo D, Petrill S, Thompson L (1994) An exploration of genetic g: hierarchical factor analysis of cognitive data from the Western Reserve Twin Project. Intelligence 18:335–347
McArdle JJ (1986) Latent variable growth within behavior genetic models. Behav Genet 16:163–200
McArdle JJ, Hamagami F (2003) Structural equation models for evaluating dynamic concepts within longitudinal twin analyses. Behav Genet 33:137–159
McArdle JJ, Grimm KJ, Hamagami F, Bowles RP, Meredith W (2009) Modeling life-span growth curves of cognition using longitudinal data with multiple samples and changing scales of measurement. Psychol Methods 14(2):126–149
McRae K, Jones M (2013) Semantic memory. In: Reisberg D (ed) The Oxford Handbook of cognitive psychology. Oxford University Press, New York, pp 206–216
Murayama K, Pekrun R, Lichtenfeld S, vom Hofe R (2013) Predicting long-term growth in students’ mathematics achievement: the unique contributions of motivation and cognitive strategies. Child Dev 84(4):1475–1490
Neale MC, McArdle JJ (2000) Structure latent growth curves for twin data. Twin Res 3:165–177
Neale MC, Boker SM, Xie G, Maes HH (2003) Mx: statistical modeling (6th edn). VCU Box 900126, Richmond, VA 23298: Department of Psychiatry
Petrill S, Luo D, Thompson L, Detterman DK (1996) The independent prediction of general intelligence by elementary cognitive tasks: genetic and environmental influences. Behav Genet 26(2):135–147
Petrill S, Hart SA, Harlaar N, Logan JAR, Justice LM, Schatschneider C, Cutting L (2010) Genetic and environmental influences on the growth of early reading skills. Child Psychol Psychiatr 51(6):660–667
Reeves CL, Bonaccio S (2011) On the myth and reality of the temporal validity degradation of general mental ability test scores. Intelligence 39:255–272
Reynolds CA, Finkel D, McArdle JJ, Gatz M, Berg S, Pedersen NL (2005) Quantitative genetic analysis of latent growth curve models of cognitive abilities in adulthood. Dev Psychol 41:3–16
Segal N (1985) Monozygotic and dizygotic Twins: a comparative analysis of mental ability profiles. Child Dev 56:1051–1058
Skibbe LE, Grimm KJ, Stanton-Chapman TL, Justice LM, Pence KL, Bowles RP (2008) Reading trajectories of children with language difficulties from preschool through fifth grade. Lang Speech Hearing Serv Sch 39(4):475–486
Tucker-Drob E (2009) Differentiation of cognitive abilities across the lifespan. Dev Psychol 45(4):1097–1118
Tucker-Drob E, Briley DA (2014) Continuity of genetic and environmental influences on cognition across the lifespan: a meta-analysis of longitudinal twin and adoption studies. Psychol Bull 140(4):949–979
Waddington CH (1942) Canalization of development and the inheritance of acquired characteristics. Nature 150:563–565
Waddington CH (1971) Concepts of development. In: Tobach E, Aronson LR, Shaw E (eds) The biopsychology of development. Academic Press, New York, pp 17–23
Wadsworth SJ, Corley RP, DeFries JC (2014) Cognitive abilities in childhood and adolescence. In: Finkel D, Reynolds CA (eds) Behavior genetics of cognition across the lifespan. Springer, New York, pp 3–40
Wechsler D (1967) Wechsler preschool and primary scale of intelligence. Psychological Corporation, New York
Wechsler D (1974) Wechsler intelligence scale for children-revised. Psychological Corporation, New York
Willoughby MT, Wirth RJ, Blair CB (2012) Executive function in early childhood: longitudinal measurement invariance and developmental change. Psychol Assess 24(2):418–431
Wilson R (1983) The Louisville Twin Study: developmental synchronies in behavior. Child Dev 54:298–316
Acknowledgments
We are grateful to the original Louisville Twin Study researchers and staff for the meticulous work they did to make it possible for us to revisit these data. This research was supported, in part, by a grant from the National Institute of Aging (1 R03 AG048850-01) and by the Department of Pediatrics at the University of Louisville.
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Deborah Finkel, Deborah Winders Davis, Eric Turkheimer, and William T. Dickens declare that they have no conflicts of interest.
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The secondary data analysis was approved by the Institution Review Board at the University of Louisville and all procedures were done in accordance with their ethical standards. Informed consent was obtained from all participants for the original data collection.
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Finkel, D., Davis, D.W., Turkheimer, E. et al. Applying Biometric Growth Curve Models to Developmental Synchronies in Cognitive Development: The Louisville Twin Study. Behav Genet 45, 600–609 (2015). https://doi.org/10.1007/s10519-015-9747-1
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DOI: https://doi.org/10.1007/s10519-015-9747-1