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Source: Springer Publishing Company
Resulting in 13 citations.
1. Averett, Susan L.
Fletcher, Erin K.
The Relationship Between Maternal Pre-pregnancy BMI and Preschool Obesity
In: Applied Demography and Public Health in the 21st Century: Volume 8 of Applied Demography Series. M.N. Hoque, B. Pecotte and M.A. McGehee, eds., Switzerland: Springer International Publishing, published online 20 October 2016: 201-219.
Also: http://link.springer.com/chapter/10.1007/978-3-319-43688-3_12
Cohort(s): Children of the NLSY79, NLSY79
Publisher: Springer
Keyword(s): Body Mass Index (BMI); Intergenerational Patterns/Transmission; Modeling, OLS; Mothers, Health; Obesity; Pre-natal Care/Exposure; Pregnancy and Pregnancy Outcomes; Preschool Children; Siblings

Permission to reprint the abstract has not been received from the publisher.

The increasing prevalence of obesity during pregnancy raises concerns over the intergenerational transmission of obesity and its potential to exacerbate the current obesity epidemic. The fetal origins hypothesis posits that the intrauterine environment might have lasting effects on children's outcomes. A large literature establishes that mother's pre-pregnancy obesity is correlated with obesity in her children. However, previous research is largely based on comparing individuals across families and hence cannot control for unobservable factors associated with both maternal and child obesity. We use both within-family comparisons and an instrumental variable approach on a sample of 4435 children to identify the effect of maternal pre-pregnancy obesity on obesity in preschool-aged children. Consistent with extant research, OLS models that rely on across-family comparisons indicate a significant correlation between maternal pre-pregnancy obesity and preschool obesity . However, maternal fixed effects render those associations insignificant. Instrumenting for mother's BMI with her sisters' BMI values confirms the null result indicating that the in utero transmission of obesity is likely not driving the increase in childhood obesity.
Bibliography Citation
Averett, Susan L. and Erin K. Fletcher. "The Relationship Between Maternal Pre-pregnancy BMI and Preschool Obesity" In: Applied Demography and Public Health in the 21st Century: Volume 8 of Applied Demography Series. M.N. Hoque, B. Pecotte and M.A. McGehee, eds., Switzerland: Springer International Publishing, published online 20 October 2016: 201-219.
2. Brand, Jennie E.
Simon Thomas, Juli
Causal Effect Heterogeneity
In: Handbook of Causal Analysis for Social Research. S. Morgan, ed., New York: Springer, 2013: 189-213
Cohort(s): NLSY79
Publisher: Springer
Keyword(s): College Education; Education; Heterogeneity; Propensity Scores; Volunteer Work

Permission to reprint the abstract has not been received from the publisher.

Individuals differ not only in background characteristics, often called “pretreatment heterogeneity,” but also in how they respond to a particular treatment, event, or intervention. A principal interaction of interest for questions of selection into treatment and causal inference in the social sciences is between the treatment and the propensity of treatment. Although the importance of “treatment-effect heterogeneity,” so defined, has been widely recognized in the causal inference literature, empirical quantitative social science research has not fully absorbed these lessons. In this chapter, we describe key estimation strategies for the study of heterogeneous treatment effects; we discuss recent research that attends to causal effect heterogeneity, with a focus on the study of effects of education, and what we gain from such attention; and we demonstrate the methods with an example of the effects of college on civic participation. The primary goal of this chapter is to encourage researchers to routinely examine treatment-effect heterogeneity with the same rigor they devote to pretreatment heterogeneity. [Chapter 11]
Bibliography Citation
Brand, Jennie E. and Juli Simon Thomas. "Causal Effect Heterogeneity" In: Handbook of Causal Analysis for Social Research. S. Morgan, ed., New York: Springer, 2013: 189-213
3. Cawley, John
Conneely, Karen
Heckman, James J.
Vytlacil, Edward
Cognitive Ability, Wages, and Meritocracy
In: Intelligence, Genes, and Success: Scientists Respond to THE BELL CURVE. B. Devlin, et al, eds., New York, NY: Springer Verlag, 1997.
Cohort(s): NLSY79
Publisher: Springer
Keyword(s): Armed Forces Qualifications Test (AFQT); Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; Demography; Education; Gender Differences; Genetics; I.Q.; Intelligence; Racial Differences; Statistical Analysis; Test Scores/Test theory/IRT; Wages

Permission to reprint the abstract has not been received from the publisher.

Previously issued as: NBER Working Paper No. W5645, Issued in July 1996. A scientific response to the best-selling The Bell Curve which set off a hailstorm of controversy upon its publication in 1994. Much of the public reaction to the book was polemic and failed to analyse the details of the science and validity of the statistical arguments underlying the book conclusion. Here, at last, social scientists and statisticians reply to The Bell Curve and its conclusions about IQ, genetics and social outcomes. Contents: Part I Overview: 1 Reexamining The Bell Curve, Stephen E. Fienberg and Daniel Resnick: 2 A Synopsis of The Bell Curve, Terry W. Belke: Part II The Genetics-Intelligence Link: 3 Of Genes and IQ, Michael Daniels, Bernie Devlin,and Kathryn Roeder: 4 The Malleability of Intelligence is Not Constrained by Heritabiligy, Douglas Waslsten: 5 Racial and Ethnic Inequalities in Health: Environmental, Psychosocial,and Physiological Pathways, Burton Singer and Carol Ryff: Part III Intelligence and the Measurement of IQ: 6 Theoretical and Technical Issues in Identifying a Factor of General Intelligence: 7 The Concept and Utility of Intelligence, Earl Hunt: 8 Is There a Cognitive Elite in America?, Nicholas Lemann: Part IV Intelligence and Success: Reanalyses of Data From the NLSY: 9 Cognitive Ability, Wages,and Meritocracy, John Cawley, Karen Conneely, James Heckman,and Edward Vytacil: 10 The Hidden Gender Restriction: The Need for Proper Controls When Testing for Racial Discrimination, Alexander Cavallo, Hazem El-Abbadi,and Randal Heeb: 11 Does Staying in School Make You Smarter? The Effect of Education on IQ in The Bell Curve, Christoper Winship and Sanders Korenman: 12 Cognitive Ability, Environmental.
Bibliography Citation
Cawley, John, Karen Conneely, James J. Heckman and Edward Vytlacil. "Cognitive Ability, Wages, and Meritocracy" In: Intelligence, Genes, and Success: Scientists Respond to THE BELL CURVE. B. Devlin, et al, eds., New York, NY: Springer Verlag, 1997.
4. Cooksey, Elizabeth C.
Using the National Longitudinal Surveys of Youth (NLSY) to Conduct Life Course Analyses
In: Handbook of Life Course Health Development. N. Halfon, C. Forrest, R. Lerner and E. Faustman, eds. Cham, Switzerland: Springer, 2018
Cohort(s): Children of the NLSY79, NLSY79, NLSY79 Young Adult, NLSY97
Publisher: Springer
Keyword(s): Health/Health Status/SF-12 Scale; Life Course

Permission to reprint the abstract has not been received from the publisher.

The National Longitudinal Surveys of Youth (NLSY) are a set of three separate US cohorts. Two of the cohorts, the NLSY79 and the NLSY97, are nationally representative, while the third, the NLSY79 Child and Young Adult cohort, follows the offspring born to female NLSY79 respondents. The NLSY79 began data collection in 1979 from an initial sample of 12,686 young men and women born between 1957 and 1964; the NLSY97 cohort, an initial group of 8984 young people born between 1980 and 1984, was first interviewed in 1997. Both the NLSY79 and NLSY97 cohorts have been interviewed annually or biennially since their inceptions. NLSY79 Child data were first obtained in 1986, when 4971 children were interviewed. Over 11,000 children have been born in total. The children have been regularly interviewed and/or assessed since 1986, many of them through their teens into their young adult years. Data for all three cohorts are remarkably suited for life course analysis due to the breadth of topical areas included in the interviews: health, education, employment, household information, family background, marital history, childcare, income and assets, attitudes, substance use, and criminal activity. The NLSY data also provide opportunities for multi-generational and kinship research. Data on health and recent research using NLSY health data are a focus of this chapter.
Bibliography Citation
Cooksey, Elizabeth C. "Using the National Longitudinal Surveys of Youth (NLSY) to Conduct Life Course Analyses" In: Handbook of Life Course Health Development. N. Halfon, C. Forrest, R. Lerner and E. Faustman, eds. Cham, Switzerland: Springer, 2018
5. Dunifon, Rachel
Kowaleski-Jones, Lori
Family Structure and Child Well-Being: The Role of Parental Social Connections
In: Fragile Families and the Marriage Agenda. L. Kowaleski-Jones and N. Wolfinger, eds., New York: Springer, 2006: 107-125
Cohort(s): Children of the NLSY79, NLSY79
Publisher: Springer
Keyword(s): Child Self-Administered Supplement (CSAS); Delinquency/Gang Activity; Family Income; Family Structure; Family, Extended; Grandparents; Household Composition; Modeling, Fixed Effects; Social Contacts/Social Network; Welfare

Permission to reprint the abstract has not been received from the publisher.

Chapter 5: Our previous work found that single-parenthood was associated with reduced wellbeing for white, but not black, children (Dunifon and Kowaleski-Jones 2002). The current paper examines whether parental social connections account for differences in the effects of family structure on child well-being. Using data from the 1979 to 2000 waves of the National Longitudinal Survey of Youth, our results show a key role for living with a grandparent in accounting for race differences in the influence of single-parenthood on children. In contrast, visiting friends and relatives did not explain differences in the relationship between single-parenthood and child delinquency among African American and families receiving public assistance sub-groups.
Bibliography Citation
Dunifon, Rachel and Lori Kowaleski-Jones. "Family Structure and Child Well-Being: The Role of Parental Social Connections" In: Fragile Families and the Marriage Agenda. L. Kowaleski-Jones and N. Wolfinger, eds., New York: Springer, 2006: 107-125
6. Farré, Lídia
Klein, Roger
Vella, Francis
A Parametric Control Function Approach to Estimating the Returns to Schooling in the Absence of Exclusion Restrictions: An Application to the NLSY
Empirical Economics 44,1 (February 2013):111-133.
Also: http://link.springer.com/article/10.1007/s00181-010-0376-5
Cohort(s): NLSY79
Publisher: Springer
Keyword(s): Educational Returns; Endogeneity; Schooling; Variables, Instrumental

Permission to reprint the abstract has not been received from the publisher.

An innovation which bypasses the need for instruments when estimating endogenous treatment effects is identification via conditional second moments. The most general of these approaches is Klein and Vella (J Econom 154:154–164, 2010), which models the conditional variances semiparametrically. While this is attractive, as identification is not reliant on parametric assumptions for variances, the nonparametric aspect of the estimation may discourage practitioners from its use. This paper outlines how the estimator can be implemented parametrically. The use of parametric assumptions is accompanied by a large reduction in computational and programming demands. We illustrate the approach by estimating the return to education using a sample drawn from the National Longitudinal Survey of Youth 1979. Accounting for endogeneity increases the estimate of the return to education from 6.8 to 11.2%.
Bibliography Citation
Farré, Lídia, Roger Klein and Francis Vella. "A Parametric Control Function Approach to Estimating the Returns to Schooling in the Absence of Exclusion Restrictions: An Application to the NLSY." Empirical Economics 44,1 (February 2013):111-133.
7. Firebaugh, Glenn
Warner, Cody
Massoglia, Michael
Fixed Effects, Random Effects, and Hybrid Models for Causal Analysis
In: Handbook of Causal Analysis for Social Research. S. Morgan, ed., New York: Springer, 2013: 113-132
Cohort(s): NLSY79
Publisher: Springer
Keyword(s): Modeling; Modeling, Fixed Effects; Modeling, Random Effects

Permission to reprint the abstract has not been received from the publisher.

Longitudinal data are becoming increasingly common in social science research. In this chapter, we discuss methods for exploiting the features of longitudinal data to study causal effects. The methods we discuss are broadly termed fixed effects and random effects models. We begin by discussing some of the advantages of fixed effects models over traditional regression approaches and then present a basic notation for the fixed effects model. This notation serves also as a baseline for introducing the random effects model, a common alternative to the fixed effects approach. After comparing fixed effects and random effects models – paying particular attention to their underlying assumptions – we describe hybrid models that combine attractive features of each. To provide a deeper understanding of these models, and to help researchers determine the most appropriate approach to use when analyzing longitudinal data, we provide three empirical examples. We also briefly discuss several extensions of fixed/random effects models. We conclude by suggesting additional literature that readers may find helpful.
Bibliography Citation
Firebaugh, Glenn, Cody Warner and Michael Massoglia. "Fixed Effects, Random Effects, and Hybrid Models for Causal Analysis" In: Handbook of Causal Analysis for Social Research. S. Morgan, ed., New York: Springer, 2013: 113-132
8. Gillespie, Brian Joseph
Household Mobility in America: Patterns, Processes, and Outcomes
Palgrave Macmillan, 2017: DOI: 10.1057/978-1-349-68271-3.
Also: http://link.springer.com/book/10.1057/978-1-349-68271-3
Cohort(s): Children of the NLSY79, NLSY79, NLSY97
Publisher: Springer
Keyword(s): Life Course; Mobility; Mobility, Residential

Permission to reprint the abstract has not been received from the publisher.

The author studies household mobility and includes multiple chapters using data from NLSY cohorts. In particular, see "Household Mobility Decisions and Location Choice" and "Individual- and Family-Level Mobility Effects" (NLSY97) and "Mobility Effects and Cumulative Mobility Contexts" (NLSY79 and Children of the NLSY79).
Bibliography Citation
Gillespie, Brian Joseph. Household Mobility in America: Patterns, Processes, and Outcomes. Palgrave Macmillan, 2017: DOI: 10.1057/978-1-349-68271-3..
9. Hair, Elizabeth Catherine
Moore, Kristin Anderson
Garrett, Sarah Bracey
Kinukawa, Akemi
Lippman, Laura
Michelson, E.
The Parent-Adolescent Relationship Scale
In: What Do Children Need to Flourish? Conceptualizing and Measuring Indicators of Positive Development, The Search Institute Series on Developmentally Attentive Community and Society, Volume 3. K. Moore and L. Lippman, eds., New York: Springer, 2005: 183-202
Cohort(s): NLSY97
Publisher: Springer
Keyword(s): Parent-Child Relationship/Closeness; Scale Construction; Teenagers

Permission to reprint the abstract has not been received from the publisher.

Papers presented at a conference held in Washington, D.C. in March 2003. Includes bibliographical references and index. This volume, part of the Search Series on Developmentally Attentive Community and Society, focuses on how scholars and practitioners can begin to build rigorous measures of the positive behaviors and attitudes that result in positive outcomes for children and youth. The volume is presented in five parts:
- Introduction and conceptual framework
- Positive formation of the self-character, values, spirituality, life satisfaction, hope, and ethnic identity
- Healthy habits, positive behaviors, and time use
- Positive relationships with parents and siblings
- Positive attitudes and behaviors toward learning and school environments
- Enacting positive values and behaviors in communities

Table of Contents
Introduction and Conceptual Framework.- The Values in Action Inventory of Character Strengths for Youth.- Adolescent Spirituality.- Children’s Life Satisfaction.- Measuring Hope in Children.- The Ethnic Identify Scale.- Leisure Time Activities in Middle Childhood.- Healthy Habits among Adolescents: Sleep, Exercise, Diet, and Body Image.- Adolescent Participation in Organized Activities.- Positive Interpersonal and Intrapersonal Functioning: An Assessment of Measures among Adolescents.- A Scale of Positive Social Behaviors.- The Parent-Adolescent Relationship Scale.- Positive Indicators of Sibling Relationship Quality: The Sibling Inventory of Behavior.- The Patterns of Adaptive Learning Survey.- Ability Self-Perceptions and Subjective Task Values in Adolescents and Children.- Assessing Academic Self-regulated Learning.- Identifying Adaptive Classrooms: Dimensions of the Classroom Social Environment.- Connection to School.- School Engagement.- Community-Based Civic Engagement.- Prosocial Orientation and Community service.- Frugality, Generosity, and Materialism in Children and Adolescents.
Bibliography Citation
Hair, Elizabeth Catherine, Kristin Anderson Moore, Sarah Bracey Garrett, Akemi Kinukawa, Laura Lippman and E. Michelson. "The Parent-Adolescent Relationship Scale" In: What Do Children Need to Flourish? Conceptualizing and Measuring Indicators of Positive Development, The Search Institute Series on Developmentally Attentive Community and Society, Volume 3. K. Moore and L. Lippman, eds., New York: Springer, 2005: 183-202
10. Halaby, Charles N.
Panel Models for the Analysis of Change and Growth in Life Course Studies
In: Handbook of the Life Course. J. Mortimer and M. Shanahan, eds., New York: Springer, 2003
Cohort(s): NLSY79
Publisher: Springer
Keyword(s): Earnings; Life Course; Modeling, Growth Curve/Latent Trajectory Analysis; School Completion; Wages, Adult

Permission to reprint the abstract has not been received from the publisher.

Panel data figure prominently in research on the many aspects of the life course. The longitudinal structure of panel data, with the properties of many units (individuals, families, etc.) measured on several occasions spread over time, is ideal for observational studies of life course processes. Panel data have proven useful for research on subjects as fundamental as the causes and consequences of marital stability and dissolution (Biblarz & Raftery 1993; Thornton, Axinn, & Teachman, 1995), the social psychological development and well-being of children and adults (Booth & Amato, 1991; Chase-Lansdale, Cherlin & Kiernan, 1995; Moen, Robison, & Dempster-McClain, 1995; Nagin & Tremblay, 1999), and the evolution of conventional (Diprete & McManus, 1996) and deviant careers (Land & Nagin, 1996; Sampson & Laub, 1992), as well as for research on the issues surrounding the timing of all these processes and related transitions. There is now widespread agreement that panel data and the analytical advances they make possible are essential for rigorously addressing the types of questions that drive and are central to many life course studies.
Bibliography Citation
Halaby, Charles N. "Panel Models for the Analysis of Change and Growth in Life Course Studies " In: Handbook of the Life Course. J. Mortimer and M. Shanahan, eds., New York: Springer, 2003
11. Moore, Kristin Anderson
Lippman, Laura
What Do Children Need to Flourish? Conceptualizing and Measuring Indicators of Positive Development
New York, NY: Springer Publishing Company, January 2005
Cohort(s): Children of the NLSY79, NLSY97
Publisher: Springer
Keyword(s): Child Health; Children, Academic Development; Children, Behavioral Development; Children, Well-Being

Permission to reprint the abstract has not been received from the publisher.

[Book Review.] What Do Children Need to Flourish? Conceptualizing and Measuring Indicators of Positive Development, part of the Search Series on Developmentally Attentive Community and Society (vol. 3), focuses on how scholars and practitioners can begin to build rigorous measures of the positive behaviors and attitudes that result in positive outcomes for children and youth. The volume is presented in five parts: - Introduction and conceptual framework
- Positive formation of the self-character, values, spirituality, life satisfaction, hope, and ethnic identity
- Healthy habits, positive behaviors, and time use
- Positive relationships with parents and siblings
- Positive attitudes and behaviors toward learning and school environments
- Enacting positive values and behaviors in communities

Table of Contents
Introduction and Conceptual Framework.- The Values in Action Inventory of Character Strengths for Youth.- Adolescent Spirituality.- Children's Life Satisfaction.- Measuring Hope in Children.- The Ethnic Identify Scale.- Leisure Time Activities in Middle Childhood.- Healthy Habits among Adolescents: Sleep, Exercise, Diet, and Body Image.- Adolescent Participation in Organized Activities.- Positive Interpersonal and Intrapersonal Functioning: An Assessment of Measures among Adolescents.- A Scale of Positive Social Behaviors.- The Parent-Adolescent Relationship Scale.- Positive Indicators of Sibling Relationship Quality: The Sibling Inventory of Behavior.- The Patterns of Adaptive Learning Survey.- Ability Self-Perceptions and Subjective Task Values in Adolescents and Children.- Assessing Academic Self-regulated Learning.- Identifying Adaptive Classrooms: Dimensions of the Classroom Social Environment.- Connection to School.- School Engagement.- Community-Based Civic Engagement.- Prosocial Orientation and Community service.- Frugality, Generosity, and Materialism in Children and Adolescents

Bibliography Citation
Moore, Kristin Anderson and Laura Lippman. What Do Children Need to Flourish? Conceptualizing and Measuring Indicators of Positive Development. New York, NY: Springer Publishing Company, January 2005.
12. Rodgers, Joseph Lee
Doughty, Debby
Does Having Boys or Girls Run in the Family?
Chance 14,4 (Fall 2001): 8-13
Cohort(s): NLSY79
Publisher: Springer
Keyword(s): Family Studies; Fertility; Genetics; Kinship; Modeling; Pairs (also see Siblings); Siblings

Permission to reprint the abstract has not been received from the publisher.

The data on which our results are based come from the National Longitudinal Survey of Youth (NLSY), a national survey with excellent family information. Our behavioral genetic study will compare respondents with different levels of relatedness to determine whether more closely related women are more similar in their children's sex composition than those more distantly related. We used twins, full siblings, half siblings, and cousin pairs -- all the pairs of which lived together in the same household -- to compare kinship kinship correlations indexing kinship similarity. If kinship pairs with higher genetic relatedness (e.g., twins) are more similar to one another than those with lower genetic relatedness (e.g., cousins), then this pattern is suggestive of a genetic influence. Our demographic study will compare sex composition patterns from the NLSY respondents to those that would be expected by chance. The model that will be fit explicitly distinguishes between stopping behavior caused by sex composition and the probability of a particular sex. These analyses will suggest whether certain patterns occur more often than chance can explain (e.g., whether there are more 'boy-biased' or 'girl-biased' families than would be expected under a binomial model).
Bibliography Citation
Rodgers, Joseph Lee and Debby Doughty. "Does Having Boys or Girls Run in the Family?" Chance 14,4 (Fall 2001): 8-13.
13. Teachman, Jay D.
Latent Growth Curve Models with Random and Fixed Effects
In: Emerging Methods in Family Research. S. McHale, P. Amato, and A. Booth, eds., Springer, National Symposium on Family Issues 4, 2014
Cohort(s): NLSY79
Publisher: Springer
Keyword(s): Body Mass Index (BMI); Modeling, Fixed Effects; Modeling, Growth Curve/Latent Trajectory Analysis; Modeling, Random Effects

Permission to reprint the abstract has not been received from the publisher.

Previous research using latent growth curve models has been within the framework of random effects. Using longitudinal data on men’s BMI taken from the National Longitudinal Study of 1979, I show that traditional latent growth curve models estimated in a random-effects framework can be extended to a fixed-effects framework. I also show that latent growth curve models can be estimated when time-constant covariates are modeled on the inter-subject level. Finally, using data taken from the Early Years of Marriage Project, I demonstrate that latent growth curve models can be used for analyzing paired data. Specifically, the latent intercept and slope terms of husbands and wives can be allowed to co-vary. (Chapter 1)
Bibliography Citation
Teachman, Jay D. "Latent Growth Curve Models with Random and Fixed Effects" In: Emerging Methods in Family Research. S. McHale, P. Amato, and A. Booth, eds., Springer, National Symposium on Family Issues 4, 2014