Pathways to Adulthood and Marriage: Teenagers’ Attitudes, Expectations, and Relationship Patterns. Endnotes
1. We excluded the small number of sample members younger than age 15 in 1999, so the sample is comparable to data from the National Survey of Family Growth, which does not survey people younger than 15.
Pathways to Adulthood and Marriage: Teenagers’ Attitudes, Expectations, and Relationship Patterns. Outline of the Report
Chapters II through IV of this report address the three research questions outlined above. Chapter V provides a summary of our main results and discusses possible directions for future research. Chapters II through IV are described in more detail below.
Pathways to Adulthood and Marriage: Teenagers’ Attitudes, Expectations, and Relationship Patterns. Data, Samples, and Methods
The limited research evidence on adolescent romantic relationships is due in part to a lack of nationally representative data. No single national data set includes all of the information needed to assess teens’ early experiences with romantic relationships, their attitudes and expectations concerning romantic relationships and marriage, and thei
Pathways to Adulthood and Marriage: Teenagers’ Attitudes, Expectations, and Relationship Patterns. Previous Research on Teens and Marriage
Previous studies of adolescent development have established that romantic relationships and dating are very common among teens. For example, data from the National Longitudinal Survey of Youth 1979 (NLSY79) Children and Young Adult Surveys indicate that more than half of all teens have had some dating experience by the time they are 16 years old a
Pathways to Adulthood and Marriage: Teenagers’ Attitudes, Expectations, and Relationship Patterns. Contents
Previous Research on Teens and Marriage
Data, Samples, and Methods
Outline of the Report
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Chapter VII: Discussion and Future Directions
In this study we have addressed a set of issues which have generally not been analyzed previously. We first examined the relationship between adolescent risky behaviors and long-term adult outcomes. Five adolescent behaviors were studied: alcohol use, marijuana use, cocaine use, sexual activity, and delinquency. Multiple outcomes were measured acr
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. References
Amato, P. R. (1999). Children of divorced parents as young adults. In E. M. Hetherington (Ed.), Coping With Divorce, Single Parenting, and Remarriage (pp. 147-164). Mahwah, NJ: Lawrence Erlbaum Associates.
Amato, P. R. (1996). Explaining the intergenerational transmission of divorce. Journal of Marriage and the Family , 58, 628-640.
Amat
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Appendix F: Regressions of Adult Outcomes on Adolescent Risky Behaviors and Other Independent Variables Among Early Initiators Living with Single Mothers at Age 14: Effects of Mothers' Education
Summary Table
Mothers' Education By Risky Behavior
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Appendix E: Regressions of Adult Outcomes on Adolescent Risky Behaviors and Other Independent Variables Among Early Initiators Living With Both Biological Parents at Age 14: Effects of Parents' Education
Summary Table
Note: Results from regressions with no differences by age are not shown.
Parents' Education by Risky Behavior
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Appendix D: Regressions of Adult Outcomes on Adolescent Risky Behaviors and Other Independent Variables Among Early Initiators: Effects of Family Structure
Note: Results from regressions with no differences by age are not shown.
Summary Table
Family Type by Risky Behavior
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Appendix C: New Categories of Risky Behavior Variables for Regressions of Different Adult Outcomes Among Early Initiators
Table C1: Definitions of Early Initiators for each Outcome/Behavior Pairing
Adult Outcomes
Age of alcohol initiation
Age of marijuana initiation
Age of cocaine initiation
Age of sex initiation
Number of crimes/delinquencies
Alcohol abuse or dependence ~ 30
11-17
11-19
11-15
11-19
9 +
Past-month drug use
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Appendix B: Regressions of Adult Outcomes on Adolescent Risky Behaviors, Family Environment, and Other Independent Variables
Table B1. Odds Ratios from Logistic Regressions of Adult Health and Crime Outcomes
Independent Variables
Adult Outcome
Health
Crime
Alcohol Abuse or Dependence Odds Ratio [P-value]
Past-month Drug Use Odds Ratio [P-value]
Ever Being in Jail Odds Ratio [P-value]
Number of observations
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Endnote
25. The creation of the variable "last time enrolled in school" takes into account the highest degree obtained by each individual respondent. An algorithm was developed to create this variable.
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Statistical Significance of Estimates
The outcome variables in this study were assumed to follow different distributions and therefore a variety of regressions were estimated. To demonstrate statistical significance of estimated results consistently and as simply as possible, we chose to show p-values for all estimates, be it odds ratios or marginal effects. P-values range from 0 to 1
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Weibull Regression
The Weibull distribution is one of the distributions used in modeling survival or duration data. The variable of interest in the analysis of duration is the length of time that elapses from the beginning of some event either until its end or until the measurement is taken, which may precede termination. In our study, we apply Weibull regression to
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Negative Binomial Regression
Negative binomial regression is used to model count dependent variables. A count variable, for example, the number of years in poverty, is assumed to follow a Poisson distribution. The Poisson distribution has the feature that its mean equals its variance. Since the variance of a count variable is often empirically larger than its mean, a situatio
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Multinomial Logistic Regression
Estimation of unordered-choice dependent variables requires a multinomial logistic model (Greene, 2000). It is intended for use when the dependent variable takes on more than two outcomes and the outcomes have no natural ordering. In our study, the family formation variable, "fertility and marital status at the age of 33", takes on six outcomes wi
The Long Term Impact of Adolescent Risky Behaviors and Family Environment. Logistic Regression
Logistic regression is used for modeling outcomes that are binary (1/0) variables. A linear probability model has a number of shortcomings in estimating binary dependent variables (Judge et al 1985, Cox and Snell, 1989). Adult outcomes that are binary in our report are alcohol abuse or dependence, past-month drug use, ever being in jail by the age
