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Author: Meredith, Kelly M.

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1.	Bard, David E. Hunter, Michael D. Beasley, William H. Rodgers, Joseph Lee Meredith, Kelly M.
1.	Biometric Nonlinear Growth Curves for Cognitive Development among NLSY Children and Youth Presented: Marseille, France, Behavior Genetics Association (BGA) Annual Meeting, June-July 2013 Cohort(s): Children of the NLSY79, NLSY79 Publisher: Behavior Genetics Association Keyword(s): Cognitive Ability; Cognitive Development; Digit Span (also see Memory for Digit Span - WISC); Kinship; Modeling, Growth Curve/Latent Trajectory Analysis; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Siblings Permission to reprint the abstract has not been received from the publisher. Recent advances in building and fitting growth curve and multi-level models that are biometrically informed (McArdle, 2006; McArdle & Plassman, 2009; McArdle & Prescott, 2005; McGue & Christensen, 2002; Reynolds, Finkel, Gatz, & Pedersen, 2002) were used to study cognitive development and decline (or slowed growth) in the National Longitudinal Survey of Youth- Child/Young Adult (NLSYC/YA) dataset. Among the highest quality outcome data in the NLSY files are indicators of cognitive ability, collected longitudinally. These data includes PIAT-Math, PIAT-Reading Recognition and PIAT-Reading Comprehension scores in a complete longitudinal stream (up to attrition) from ages 5 to 14, as well as PPVT verbal abilities, Digit Span scores, and cognitive developmental milestone indicators during toddler and preschool years. Building off of longitudinal methodologies outside of behavior genetics (Grimm, Ram, & Hamagami, 2011; McArdle, Ferrer-Caja, Hamagami, & Woodcock, 2002; Pinheiro & Bates, 2000), this empirical application will also contribute to biometric analytic developments utilizing "fully" nonlinear (e.g., exponential; Davidian & Giltinan, 1995) growth models that better capture developmental and aging-related changes in cognition. Multivariate models were also examined to explore cognitive mediational hypotheses of whether early cognitive milestones could predict later developmental trajectories of PIAT, PPVT, and Digit Span growth. These models predicted both variation in level effects (early age ability level) and growth/decline effects over time (developmental changes in cognition). Motivation for these analyses closely coincide with the convergence of evidence surrounding critical periods of development between the ages of 0 and 5 (Shonkoff & Phillips, 2000). Again, interest will move beyond simple associations of early cognition and childhood cognitive development to questions of whether individual differences in genetic or environmental sources of variance best explain these associations via multivariate biometric mediation modeling.
	Bibliography Citation Bard, David E., Michael D. Hunter, William H. Beasley, Joseph Lee Rodgers and Kelly M. Meredith. "Biometric Nonlinear Growth Curves for Cognitive Development among NLSY Children and Youth." Presented: Marseille, France, Behavior Genetics Association (BGA) Annual Meeting, June-July 2013.

2.	Beasley, William H. Bard, David E. Hunter, Michael D. Meredith, Kelly M. Rodgers, Joseph Lee
2.	NLSY Kinship Links: Creating Biometrical Design Structures from Cross-Generational Data Presented: Marseille, France, Behavior Genetics Association (BGA) Annual Meeting, June-July 2013 Cohort(s): Children of the NLSY79, NLSY79, NLSY97 Publisher: Behavior Genetics Association Keyword(s): Cognitive Ability; Cognitive Development; Digit Span (also see Memory for Digit Span - WISC); Genetics; Kinship; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Siblings Permission to reprint the abstract has not been received from the publisher. In this paper, we present innovative NLSY designs. We begin with a review of the Mother-Daughter-Aunt-Niece (MDAN) design (Rodgers et al. 2008) and expand this to include other relationships simultaneously, including the 5,000 NLSYC first cousins. Following we discuss the potential for limited three-generational designs using the available information about the parents of the original NLSY79 respondents. Finally, we discuss how incorporating a third dataset, (the NLSY97) provides a ‘"phantom mother’" design, developed by (age, SES, family, etc.) matching of the NLSYC to the NLSY97 respondents, and assigning NLSY79 mothers to NLSY97 respondents across these matches.
	Bibliography Citation Beasley, William H., David E. Bard, Michael D. Hunter, Kelly M. Meredith and Joseph Lee Rodgers. "NLSY Kinship Links: Creating Biometrical Design Structures from Cross-Generational Data." Presented: Marseille, France, Behavior Genetics Association (BGA) Annual Meeting, June-July 2013.

3.	Hunter, Michael D. Bard, David E. Beasley, William H. Meredith, Kelly M. Rodgers, Joseph Lee
3.	A Dynamic Mixture Biometric Model of Cognitive Development in the NLSY Children Presented: Charlottesville VA, Behavior Genetics Association Annual Meeting, June 2014 Cohort(s): Children of the NLSY79 Publisher: Behavior Genetics Association Keyword(s): Digit Span (also see Memory for Digit Span - WISC); Genetics; Kinship; Modeling, Multilevel; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Siblings Permission to reprint the abstract has not been received from the publisher. A novel method of combining within-person and between-person variability in a biometrically informed model was used to examine nonlinear cognitive development in the National Longitudinal Survey of Youth-Child/Young Adult (NLSYC/YA) dataset. Entirely within person biometric models (e.g. Molenaar 2010) can be fit, but generally assume that all persons are heterogeneous. By contrast, conventional between-person biometric models (e.g. Martin & Eaves 1977) make the opposite assumption: that the sample is uniformly homogeneous. State space mixture modeling (SSMMing) is a middle ground. SSMMs make a within-person longitudinal biometric model for each pair of genetically related participants to account for the idiographic nature of genetic and developmental variability (Nesselroade, Gerstorf, Hardy, and Ram 2007; Molenaar, Boomsma, and Dolan 1993). Simultaneously, SSMMs allow for a finite number of groups that are within-group homogeneous and between-group heterogeneous to allow for uniformity in development among some people. The longitudinal model in SSMMs has both autoregressive and linear slope components with individually estimated growth trajectories. Hence, nonlinear patterns of change are allowed in the context of linear modeling. Five longitudinally measured cognitive variables (PIAT Reading Recognition, Reading Comprehension, and Math; PPVT; and Digit Span) from the NLSYC are used both to illustrate SSMMs as a method and to provide insight into this important process. The finding that cognitive ability is highly heritable between individuals was replicated in cross-sectional subsets of the NLSYC. However, the within-person longitudinal model showed minimal contribution from additive genetic variance across the five cognitive variables. A SSMM with two groups found a small subgroup in which cognitive ability was heritable within persons, but for the majority of individuals studied the intraindividual variance was dominated by common and specific environmental factors. The structure of intraindividual heritability of cognitive ability thus appears quite different from that found in conventional between person biometric modeling.
	Bibliography Citation Hunter, Michael D., David E. Bard, William H. Beasley, Kelly M. Meredith and Joseph Lee Rodgers. "A Dynamic Mixture Biometric Model of Cognitive Development in the NLSY Children." Presented: Charlottesville VA, Behavior Genetics Association Annual Meeting, June 2014.

4.	Meredith, Kelly M.
4.	Is AFI All in the Family? A Multi-Level Family Study of Age of First Intercourse Ph.D. Dissertation, Department of Psychology, University of Oklahoma, 2013. Also: https://shareok.org/handle/11244/7913 Cohort(s): Children of the NLSY79, NLSY79, NLSY79 Young Adult Publisher: Department of Psychology, University of Oklahoma Keyword(s): Adolescent Sexual Activity; Age at First Intercourse; Family Influences; Home Environment; Intelligence; Intergenerational Patterns/Transmission; Modeling, Multilevel; Siblings Permission to reprint the abstract has not been received from the publisher. The importance of the timing of first intercourse in one's life history, and its significance in relation to a number of fertility and social outcomes, has been established in a number of studies. Studies have attempted to untangle the factors that contribute to its timing, and only some of these studies explore the possibility of selection influences on this outcome. This study uses National Longitudinal Survey of Youth (NLSY) samples and multilevel survival models to evaluate predictors of age at first intercourse (AFI) at both the family and individual level. The family structure among the NLSY samples enables the use of a children of siblings type design so that we may also investigate the possible influence of selection effects. Intelligence and educational goals are often implicated as factors motivating adolescents and young adults to delay AFI. Extended family, maternal, and child intelligence variables are the predictor variables of focus in this study. Other variables include maternal AFI, measures of the home environment, and family income, as these variables also relate to the evaluation of educational goals. Gender and race are also included as control variables. None of the intelligence variables were found to be significant predictors of AFI, though interesting trends emerged. Maternal AFI was consistently a significant predictor across models, but was later identified as non-significant relative to average AFI at the maternal family level. Possible explanations for these findings are offered.
	Bibliography Citation Meredith, Kelly M. Is AFI All in the Family? A Multi-Level Family Study of Age of First Intercourse. Ph.D. Dissertation, Department of Psychology, University of Oklahoma, 2013..

5.	Rodgers, Joseph Lee Beasley, William H. Bard, David E. Meredith, Kelly M. Hunter, Michael D. Johnson, Amber Buster, Maury Allen Li, Chengchang
5.	The NLSY Kinship Links: Using the NLSY79 and NLSY-Children Data to Conduct Genetically-Informed and Family-Oriented Research Behavior Genetics 46,4 (July 2016): 538-551. Also: http://link.springer.com/article/10.1007/s10519-016-9785-3 Cohort(s): Children of the NLSY79, NLSY79 Publisher: Behavior Genetics Association Keyword(s): Body Mass Index (BMI); Data Quality/Consistency; Genetics; Height; Intergenerational Patterns/Transmission; Kinship; Modeling, Multilevel; Siblings; Weight Permission to reprint the abstract has not been received from the publisher. The National Longitudinal Survey of Youth datasets (NLSY79; NLSY-Children/Young Adults; NLSY97) have extensive family pedigree information contained within them. These data sources are based on probability sampling, a longitudinal design, and a cross-generational and within-family data structure, with hundreds of phenotypes relevant to behavior genetic (BG) researchers, as well as to other developmental and family researchers. These datasets provide a unique and powerful source of information for BG researchers. But much of the information required for biometrical modeling has been hidden, and has required substantial programming effort to uncover--until recently. Our research team has spent over 20 years developing kinship links to genetically inform biometrical modeling. In the most recent release of kinship links from two of the NLSY datasets, the direct kinship indicators included in the 2006 surveys allowed successful and unambiguous linking of over 94 % of the potential pairs. In this paper, we provide details for research teams interested in using the NLSY data portfolio to conduct BG (and other family-oriented) research.
	Bibliography Citation Rodgers, Joseph Lee, William H. Beasley, David E. Bard, Kelly M. Meredith, Michael D. Hunter, Amber Johnson, Maury Allen Buster and Chengchang Li. "The NLSY Kinship Links: Using the NLSY79 and NLSY-Children Data to Conduct Genetically-Informed and Family-Oriented Research." Behavior Genetics 46,4 (July 2016): 538-551.

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