Behavior Genetics

, Volume 38, Issue 6, pp 567–578 | Cite as

The Cross-Generational Mother–Daughter–Aunt–Niece Design: Establishing Validity of the MDAN Design with NLSY Fertility Variables

  • Joseph Lee RodgersEmail author
  • David E. Bard
  • Amber Johnson
  • Brian D’Onofrio
  • Warren B. Miller
Original Research


Using National Longitudinal Survey of Youth (NLSY) fertility variables, we introduce and illustrate a new genetically-informative design. First, we develop a kinship linking algorithm, using the NLSY79 and the NLSY-Children data to link mothers to daughters and aunts to nieces. Then we construct mother–daughter correlations to compare to aunt–niece correlations, an MDAN design, within the context of the quantitative genetic model. The results of our empirical illustration, which uses DF Analysis and generalized estimation equations (GEE) to estimate biometrical parameters from NLSY79 sister–sister pairs and their children in the NLSY-Children dataset, provide both face validity and concurrent validity in support of the efficacy of the design. We describe extensions of the MDAN design. Compared to the typical within-generational design used in most behavior genetic research, the cross-generational feature of this design has certain advantages and interesting features. In particular, we note that the equal environment assumption of the traditional biometrical model shifts in the context of a cross-generational design. These shifts raise questions and provide motivation for future research using the MDAN and other cross-generational designs.


Behavior genetic designs Fertility precursors NLSY79 NLSY-children Siblings Aunts Family designs Heritability DF Analysis 


  1. Bard DE, Rodgers JL (2006) Use of discrete-time survival analysis for modeling multivariate ACE models of fertility precursors from the children of the NLSY. Poster presented at the June, 2006 meetings of the Behavior Genetic Association, Storrs, CNGoogle Scholar
  2. Baydar N, Greek A (2001) Analysis of data from related individuals. Working paper, Battell Centers for Public Health Research and Evaluation, Seattle WAGoogle Scholar
  3. Bouchard TJ, Lykken DT, McGue M, Segal NL, Tellegen A (1990) Sources of human psychological differences: the Minnesota Study of Twins Reared Apart. Science 250:223–228. doi: 10.1126/science.2218526 PubMedCrossRefGoogle Scholar
  4. Bricker JB, Stallings MC, Corley RP, Wadsworth SJ, Bryan A, Timberlake DS, Hewitt JK, Caspi A, Hofer SM, Rhea SA, DeFries JC (2006) Genetic and environmental influences on age at sexual initiation in the Colorado adoption project. Behav Genet 36:820–832. doi: 10.1007/s10519-006-9079-2 PubMedCrossRefGoogle Scholar
  5. Brooks-Gunn J, Warren MP, Rosso J, Gargiulo J (1987) Validity of self-report measures of girls’ pubertal status. Child Dev 58:829–841. doi: 10.2307/1130220 PubMedCrossRefGoogle Scholar
  6. Center for Human Resource Research (2006) NLSY79 child & young adult data users guide. Center for Human Resource Research, ColumbusGoogle Scholar
  7. Chase-Lansdale PL, Mott FL, Brooks-Gunn J, Phillips DA (1991) Children of the National Longitudinal Survey of Youth: a unique research opportunity. Dev Psychol 27:918–931. doi: 10.1037/0012-1649.27.6.918 CrossRefGoogle Scholar
  8. Cherny SS, DeFries JC, Fulker DW (1992) Multiple regression of twin data: a model-fitting approach. Behav Genet 22:489–497. doi: 10.1007/BF01066617 PubMedCrossRefGoogle Scholar
  9. Damon A, Damon ST, Reed RB, Valadian I (1969) Age at menarche of mothers and daughters with a note on accuracy of recall. Hum Biol 38:255–273Google Scholar
  10. DeFries JC, Fulker DW (1985) Multiple regression analysis of twin data. Behav Genet 15:467–473. doi: 10.1007/BF01066239 PubMedCrossRefGoogle Scholar
  11. D’Onofrio BM, Turkheimer EN, Eaves LJ, Corey LA, Berg K, Solaas MH, Emery RE (2003). J Child Psychol Psychiatry Allied Discipl 44:1130–1144. doi:10.1111/1469-7610.00196 Google Scholar
  12. D’Onofrio BM, Van Hulle CA, Waldman ID, Rodgers JL, Rathouz PJ, Lahey BB (2007) Causal inferences regarding prenatal alcohol exposure and childhood externalizing problems. Arch Gen Psychiatry 64:1296–1304. doi: 10.1001/archpsyc.64.11.1296 PubMedCrossRefGoogle Scholar
  13. Doughty D, Rodgers JL (2000) Behavior genetic modeling of menarche in U.S. females. In: Rodgers JL, Rowe D, Miller WB (eds) Genetic influences on fertility and sexuality. Kluwer Academic Press, BostonGoogle Scholar
  14. Dunlop DD (1994) Regression for longitudinal data: a bridge from least squares regression. Am Stat 48:299–303. doi: 10.2307/2684838 CrossRefGoogle Scholar
  15. Evans DM, Gillespie NA, Martin NG (2002) Biometrical genetics. Biol Psychol 61:33–51. doi: 10.1016/S0301-0511(02)00051-0 PubMedCrossRefGoogle Scholar
  16. Falconer DS (1979) Introduction to quantitative genetics. Longman, New YorkGoogle Scholar
  17. Fisher RF (1930) The genetical theory of natural selection. Clarendon Press, OxfordGoogle Scholar
  18. Fisher RF (1935) The design of experiments. Olyver and Boyd, EdinburghGoogle Scholar
  19. Gottesman II, Bertelsen A (1989) Confirming unexpressed genotypes for schizophrenia. Arch Gen Psychiatry 46:867–872PubMedGoogle Scholar
  20. Guo G, Wang JM (2002) The mixed or multilevel models for behavior genetic analysis. Behav Genet 32:37–49. doi: 10.1023/A:1014455812027 PubMedCrossRefGoogle Scholar
  21. Harden KP, Turkheimer E, Emery RE, D’Onofrio BM, Slutske WS, Heath AC, Martin NG (2007) Marital conflict and conduct problems in children of twins. Child Dev 78:1–18. doi: 10.1111/j.1467-8624.2007.00982.x PubMedCrossRefGoogle Scholar
  22. Hardin JW, Hilbe JM (2003) Generalized estimating equations. Chapman & Hall/CRC, Boca RatonGoogle Scholar
  23. Heath AC, Kendler AS, Eaves LJ, Markell D (1985) The resolution of cultural and biological inheritance: Informativeness of different relationships. Behav Genet 15:439–465. doi: 10.1007/BF01066238 PubMedCrossRefGoogle Scholar
  24. Huber PJ (1967) The behavior of maximum likelihood estimates under non-standard conditions. In Proceedings of the fifth Berkeley symposium on mathematical statistics and probability, vol 1, pp 221–233Google Scholar
  25. Hughes KA, Burleson MH (2000) Evolutionary causes of genetic variation in fertility and other fitness components. In: Rodgers JL, Rowe DC, Miller WB (eds) Genetic influences on human fertility and sexuality. Kluwer, Boston, pp 7–34Google Scholar
  26. Jinks JL, Fulker DW (1970) A comparison of the biometrical-genetical, MAVA and classical approaches to the analysis of human behavior. Psychol Bull 73:311–349. doi: 10.1037/h0029135 PubMedCrossRefGoogle Scholar
  27. Kirk KM, Blomberg SP, Duffy DL, Heath AC, Owens IPF, Martin NG (2000) Natural selection and quantitative genetics of life history traits in western women: a twin study. Evol Int J Org Evol 55:423–435Google Scholar
  28. Kohler H-P, Rodgers JL (1999) DF analysis of binary, ordered, and censored variables using probit and tobit approaches. Behav Genet 29:221–232. doi: 10.1023/A:1021686005855 CrossRefGoogle Scholar
  29. Kohler H-P, Rodgers JL (2001) DF-analysis of heritability with double-entry twin data: Asymptotic standard errors and efficient estimation. Behav Genet 31:179–192. doi: 10.1023/A:1010253411274 PubMedCrossRefGoogle Scholar
  30. Kohler H-P, Rodgers JL, Miller WB, Skytthe A, Christensen K (2006) Bio-social determinants of fertility. Int J Androl 29:46–53. doi: 10.1111/j.1365-2605.2005.00606.x PubMedCrossRefGoogle Scholar
  31. LaBuda MC, DeFries JC (1990) Genetic etiology of reading disability: Evidence from a twin study. In: Pavlidis GT (ed) Persepctives on dyslexia, vol 1. Wiley, New York, pp 47–76Google Scholar
  32. Liang K-Y, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73:13–22. doi: 10.1093/biomet/73.1.13 CrossRefGoogle Scholar
  33. Loehlin JC (1989) Partitioning environmental and genetic contributions to behavioral development. Am Psychol 44:1285–1292. doi: 10.1037/0003-066X.44.10.1285 PubMedCrossRefGoogle Scholar
  34. Magnus P, Berg K, Bjerkedal T (1985) No significant difference in birth weight for offspring of weight discordant monozygotic female twins. Early Hum Dev 12:55–59. doi: 10.1016/0378-3782(85)90137-9 PubMedCrossRefGoogle Scholar
  35. McArdle JJ, Prescott CA (2005) Mixed-effects variance components models for biometrical family analyses. Behav Genet 35:631–652. doi: 10.1007/s10519-005-2868-1 PubMedCrossRefGoogle Scholar
  36. McCartan LM (2007) Inevitable, influential, or unnecessary? Exploring the utility of genetic explanation for delinquent behavior. J Crim Just 35:219–233. doi: 10.1016/j.jcrimjus.2007.01.008 CrossRefGoogle Scholar
  37. Mendle J, Turkheimer E, D’Onofrio BM, Lynch SK, Emergy RE, Slutske WS, Martin NG (2006) Family structure and age at menarche: a children-of-twins approach. Dev Psychol 42:533–542. doi: 10.1037/0012-1649.42.3.533 PubMedCrossRefGoogle Scholar
  38. Moffitt TE, Caspi A, Belsky J, Silva PA (1992) Childhood experience and the onset of menarche: a test of a sociobiological model. Child Dev 63:47–58. doi: 10.2307/1130900 PubMedCrossRefGoogle Scholar
  39. Nance WE, Corey LA (1976) Genetic models for the analysis of data from the families of identical twins. Genetics 83:811–826PubMedGoogle Scholar
  40. Neale MC, Cardon LR (1992) Methodology for genetic studies of twins and families. Kluwer Academic Press, DordrechtGoogle Scholar
  41. Plomin R (1990) Nature and nurture: an introduction to human behavior genetics. Brooks/Cole, Pacific GroveGoogle Scholar
  42. Plomin R, DeFries JC, McClearn GE (1990) Behavior genetics: a primer. Freeman and Company, New YorkGoogle Scholar
  43. Purcell S, Koenen KC (2005) Environmental mediation and the twin design. Behav Genet 35:491–498. doi: 10.1007/s10519-004-1484-9 PubMedCrossRefGoogle Scholar
  44. Purcell S, Sham PC (2003) A model-fitting implementation of the DeFries–Fulker model for selected twin data. Behav Genet 33:271–278. doi: 10.1023/A:1023494408079 PubMedCrossRefGoogle Scholar
  45. Rodgers JL (1996) NLSY Youth linking algorithm. Internal DocumentGoogle Scholar
  46. Rodgers JL, Kohler H-P (eds) (2003) The biodemography of human reproduction and fertility. Kluwer Academic Publishers, BostonGoogle Scholar
  47. Rodgers JL, Kohler H-P (2005) Reformulating and simplifying the DF Analysis model. Behav Genet 35:211–217. doi: 10.1007/s10519-004-1020-y CrossRefGoogle Scholar
  48. Rodgers JL, McGue M (1994) A simple algebraic demonstration of the validity of DeFries–Fulker analysis in unselected samples with multiple kinship levels. Behav Genet 24:259–263. doi: 10.1007/BF01067192 PubMedCrossRefGoogle Scholar
  49. Rodgers JL, Billy JO, Udry JR (1982) The rescission of behaviors: inconsistent responses in adolescent sexuality data. Soc Sci Res 11:280–296. doi: 10.1016/0049-089X(82)90012-6 CrossRefGoogle Scholar
  50. Rodgers JL, Harris D, Vickers KB (1992) Seasonality of onset of adolescent coitus. Soc Biol 39:1–14PubMedGoogle Scholar
  51. Rodgers JL, Rowe DC, Li C (1994a) Beyond nature versus nurture: DF analysis of nonshared influences on problem behaviors. Dev Psychol 30:374–384. doi: 10.1037/0012-1649.30.3.374 CrossRefGoogle Scholar
  52. Rodgers JL, Rowe DC, May K (1994b) DF analysis of NLSY IQ/achievement data: nonshared environmental influences. Intelligence 19:157–177. doi: 10.1016/0160-2896(94)90011-6 CrossRefGoogle Scholar
  53. Rodgers JL, Rowe DC, Buster M (1999) Nature, nurture, and first sexual intercourse in the USA: fitting behavioral genetic models to NLSY kinship data. J Biosocial Sci 31:29–41.Google Scholar
  54. Rodgers JL, Rowe DC, Miller WB (eds) (2000) Genetic influences on human fertility and sexuality: theoretical and empirical contributions from the biological and behavioral sciences. Kluwer Academic Publishers, BostonGoogle Scholar
  55. Rodgers JL, Hughes K, Kohler H-P, Christensen K, Doughty D, Rowe DC, Miller WB (2001a) Genetic influence helps explain variation in human fertility: evidence from recent behavioral and molecular genetic studies. Curr Dir Psychol Sci 10:184–188. doi: 10.1111/1467-8721.00145 CrossRefGoogle Scholar
  56. Rodgers JL, Buster M, Rowe DC (2001b) Genetic and environmental influences on delinquency: DF analysis of NLSY kinship data. J Quant Criminol 17:145–168. doi: 10.1023/A:1011097929954 CrossRefGoogle Scholar
  57. Rodgers JL, Kohler H-P, Kyvik K, Christensen K (2001c) Behavior genetic modeling of human fertility: findings from a contemporary Danish twin study. Demography 38:29–42. doi: 10.1353/dem.2001.0009 PubMedCrossRefGoogle Scholar
  58. Rodgers JL, Johnson A, Bard DE (2005) NLSY-Children/Young Adult (1986–2000) kinship linking algorithm. Internal documentGoogle Scholar
  59. Rodgers JL, Bard DE, Miller WB (2007) Multivariate cholesky models of human female fertility patterns in the NLSY. Behav Genet 37:345–361. doi: 10.1007/s10519-006-9137-9 PubMedCrossRefGoogle Scholar
  60. Segal N, McGuire J, Havlena PG (2006) IQ similarity in virtual twins: Developmental trends. Paper presented at the June, 2006, meetings of the Behavior Genetic Association, Storrs, CNGoogle Scholar
  61. Shadish WR, Cook TD, Campbell DT (2002) Experimental and quasi-experimental designs for generalized causal inference. Houghton-Mifflin, BostonGoogle Scholar
  62. Siegel DM, Aten MJ, Roughmann KJ (1998) Self-reported honesty among middle and high school students responding to a sexual behavior questionnaire. J Adolesc Health 23:20–28. doi: 10.1016/S1054-139X(97)00274-7 PubMedCrossRefGoogle Scholar
  63. Silberg JL, Eaves LJ (2004) Analyzing the contribution of genes and parent-child interaction to childhood behavioral and emotional problems: a model for the children of twins. Psychol Med 34:347–356. doi: 10.1017/S0033291703008948 PubMedCrossRefGoogle Scholar
  64. Truett KR, Eaves LJ, Waiters EE, Heath AC, Hewitt JK, Meyer JM, Silberg J, Neale MC, Martin NG, Kendler KS (1994) A model system for analysis of family resemblance in extended kinships of twins. Behav Genet 24:35–49. doi: 10.1007/BF01067927 PubMedCrossRefGoogle Scholar
  65. Trumbetta SL, Markowitz EM, Gottesman II (2007) Marriage and genetic variation across the lifespan: not a steady relationship? Behav Genet 37:362–375. doi: 10.1007/s10519-006-9132-1 PubMedCrossRefGoogle Scholar
  66. Udry JR (1996) Biosocial models of low-fertility societies. In: Casterline JB, Lee RD, Foote KA (eds) Fertility in the United States: new patterns, new theories. The Population Council, New YorkGoogle Scholar
  67. Upchurch DM, Lillard LA, Aneshensel CS, Li NF (2002) Inconsistencies in reporting the occurrence and timing of first intercourse among adolescents. J Sex Res 39:197–206PubMedCrossRefGoogle Scholar
  68. van den Oord EJCG (2001) Estimating effects of latent and measured genotypes in multilevel models. Stat Methods Med Res 10:393–407. doi: 10.1191/096228001682157625 PubMedCrossRefGoogle Scholar
  69. van den Oord EJCG, Rowe DC (1997) Continuity and change in children’s social maladjustment: A developmental behavior genetic study. Dev Psychol 33:319–332. doi: 10.1037/0012-1649.33.2.319 PubMedCrossRefGoogle Scholar
  70. van den Oord EJCG, Rowe DC (2000) Racial differences in birth health risk: a quantitative genetic approach. Demography 37:285–298. doi: 10.2307/2648042 PubMedCrossRefGoogle Scholar
  71. Van Hulle CA, Rodgers JL, D’Onofrio BM, Waldman ID, Lahey BB (2007) Sex differences in the causes of self-reported adolescent delinquency. J Abnorm Psychol 116:236–248. doi: 10.1037/0021-843X.116.2.236 PubMedCrossRefGoogle Scholar
  72. Waller NB (1994) A DeFries and Fulker regression model for genetic nonadditivity. Behav Genet 24:149–153. doi: 10.1007/BF01067818 PubMedCrossRefGoogle Scholar
  73. White H (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48:817–838. doi: 10.2307/1912934 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Joseph Lee Rodgers
    • 1
    Email author
  • David E. Bard
    • 2
  • Amber Johnson
    • 3
  • Brian D’Onofrio
    • 4
  • Warren B. Miller
    • 5
  1. 1.Department of PsychologyUniversity of OklahomaNormanUSA
  2. 2.University of Oklahoma Health Sciences CenterOklahoma CityUSA
  3. 3.Portland State UniversityPortlandUSA
  4. 4.University of IndianaBloomingtonUSA
  5. 5.Transnational Family Research InstituteBethesdaUSA

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