Parental Monitoring Deters Adolescent Sexual Initiation: Discrete-Time Survival Mixture Analysis

2010 ◽  
Author(s):  
David Huang ◽  
Debra A. Murphy ◽  
Yih-Ing Hser
Keyword(s):  
Discrete Time ◽  
Parental Monitoring ◽  
Sexual Initiation ◽  
Mixture Analysis ◽  
Survival Mixture Analysis

scholarly journals Influences of victimization and comorbid conditions on substance use disorder outcomes in justice-involved youth: A discrete time survival mixture analysis

2019 ◽  
Vol 32 (3) ◽  
pp. 1045-1058 ◽  
Author(s):  
Jordan P. Davis ◽  
Tim Janssen ◽  
Emily R. Dworkin ◽  
Tara M. Dumas ◽  
Jeremy Goldbach ◽  
...  
Keyword(s):  
Substance Use ◽  
Juvenile Offenders ◽  
Substance Use Disorder ◽  
Discrete Time ◽  
Growth Mixture Modeling ◽  
Substance Use Prevention ◽  
Mixture Analysis ◽  
Growth Mixture ◽  
Treatment Entry ◽  
Survival Mixture Analysis

AbstractTo understand how exposure to victimization during adolescence and the presence of comorbid psychological conditions influence substance use treatment entry and substance use disorder diagnosis from 14 to 25 years old among serious juvenile offenders, this study included 1,354 serious juvenile offenders who were prospectively followed over 7 years. Growth mixture modeling was used to assess profiles of early victimization during adolescence (14–17 years). Discrete time survival mixture analysis was used to assess time to treatment entry and substance use disorder diagnosis. Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) were used as predictors of survival time. Mixture models revealed three profiles of victimization: sustained poly-victimization, moderate/decreasing victimization, and low victimization. Youth in the sustained poly-victimization class were more likely to enter treatment earlier and have a substance use diagnosis earlier than other classes. PTSD was a significant predictor of treatment entry for youth in the sustained poly-victimization class, and MDD was a significant predictor of substance use disorder diagnosis for youth in the moderate/decreasing victimization class. Therefore, substance use prevention programming targeted at youth experiencing poly-victimization in early adolescence—especially those who have PTSD or MDD—is needed.

Cumulative Risk for Early Sexual Initiation Among American Indian Youth: A Discrete-Time Survival Analysis

2007 ◽  
Vol 17 (2) ◽  
pp. 387-412 ◽  
Author(s):  
Christina M. Mitchell ◽  
Nancy Rumbaugh Whitesell ◽  
Paul Spicer ◽  
Janette Beals ◽  
Carol E. Kaufman ◽  
...  
Keyword(s):  
Survival Analysis ◽  
American Indian ◽  
Discrete Time ◽  
Cumulative Risk ◽  
Sexual Initiation ◽  
American Indian Youth ◽  
Early Sexual Initiation ◽  
Discrete Time Survival Analysis

scholarly journals The Influence of Parental Monitoring on Adolescent Sexual Initiation

2005 ◽  
Vol 159 (8) ◽  
pp. 724 ◽  
Author(s):  
John A. Sieverding ◽  
Nancy Adler ◽  
Stephanie Witt ◽  
Jonathan Ellen
Keyword(s):  
Parental Monitoring ◽  
Sexual Initiation

Sexual Initiation in Early Adolescence: The Nexus of Parental and Community Control

2005 ◽  
Vol 70 (5) ◽  
pp. 758-778 ◽  
Author(s):  
Christopher R. Browning ◽  
Tama Leventhal ◽  
Jeanne Brooks-Gunn
Keyword(s):  
Human Development ◽  
Collective Efficacy ◽  
Early Adolescence ◽  
Urban Youth ◽  
Parental Monitoring ◽  
Sexual Initiation ◽  
Community Control ◽  
First Intercourse ◽  
Neighborhood Collective Efficacy ◽  
Sexual Onset

This study explores the link between neighborhood collective efficacy and the timing of first intercourse for a sample of urban youth. The authors hypothesize that youth who experience lower levels of parental monitoring and higher levels of exposure to neighborhood environments are more likely to be influenced by collective supervision capacity. The study also examines the extent to which parental and neighborhood controls differ in their impact on first intercourse experiences by gender. Analyses of multilevel and longitudinal data from the Project on Human Development in Chicago Neighborhoods indicate that neighborhood collective efficacy delays sexual onset only for adolescents who experience lower levels of parental monitoring. Although parental monitoring exerts significantly greater influence on girls' timing of first intercourse, the moderating effect of parental monitoring on collective efficacy holds for both boys and girls.

The Effect of Partly Missing Covariates on Statistical Power in Randomized Controlled Trials With Discrete-Time Survival Endpoints

Methodology ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 41-60
Author(s):  
Shahab Jolani ◽  
Maryam Safarkhani
Keyword(s):  
Randomized Controlled Trials ◽  
Discrete Time ◽  
Treatment Effect ◽  
Survival Data ◽  
Controlled Trials ◽  
Missing Covariates ◽  
Indicator Method ◽  
Imputation Methods ◽  
Randomized Controlled ◽  
Baseline Covariates

Abstract. In randomized controlled trials (RCTs), a common strategy to increase power to detect a treatment effect is adjustment for baseline covariates. However, adjustment with partly missing covariates, where complete cases are only used, is inefficient. We consider different alternatives in trials with discrete-time survival data, where subjects are measured in discrete-time intervals while they may experience an event at any point in time. The results of a Monte Carlo simulation study, as well as a case study of randomized trials in smokers with attention deficit hyperactivity disorder (ADHD), indicated that single and multiple imputation methods outperform the other methods and increase precision in estimating the treatment effect. Missing indicator method, which uses a dummy variable in the statistical model to indicate whether the value for that variable is missing and sets the same value to all missing values, is comparable to imputation methods. Nevertheless, the power level to detect the treatment effect based on missing indicator method is marginally lower than the imputation methods, particularly when the missingness depends on the outcome. In conclusion, it appears that imputation of partly missing (baseline) covariates should be preferred in the analysis of discrete-time survival data.

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