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Home » Events » Past Conferences » 2011 NCFR Annual Conference » Conference Schedule » Conference Schedule by Day » 11.15.2011
Methods in Research on Adolescents
TCRM Workshop Sessions 4
Session ID#:
014-TC4A Discussants: David Johnson and J. Kelly McCoy
Presider: Rebekah Young
Date:
Tuesday, November 15, 2011Time:
4:45 pm - 6:15 pm
Session Location:
Salon 13 Session Type: Paper, TCRM
About the Session
Presented by: Clinton G. Gudmunson, Randal Day, Ivan F. Beutler
Presented by: Clinton G. Gudmunson, Randal Day, Ivan F. Beutler
This study describes the measurement properties of a new money-attitudes scale measuring adolescent entitlement, and begins to explore its predictive validity in family and peer-based contexts. This study moves our investigation of adolescent entitlement attitudes on from pilot testing with convenience samples (Beutler & Gudmunson, in review) on to examination using longitudinal panel data from a probability sample of households from three waves of the Flourishing Families Project. Results of structural equations suggest that entitlement attitudes are features of psychosocially active family environments; family religious practices in the home forestall entitlement attitudes whereas psychologically controlling parents foster the development of entitlement attitudes. These processes have implications for specific forms of adolescent psychosocial well-being and association with prosocial and delinquent peers. Modeling Early Alcohol Initiation:L A Comparison of Ordinary Least Squares Regression and Discrete Time Multilevel Survival Analysis Presented by: Ketevan Daniela, Ronald B. Cox, Jr., Robert E. Larzelere
Scope and Method of Study: In social science research there is often a need to study the occurrence of a rare event whose distribution is not normal and whose data structure is nested. Common statistical methods for these questions require either the violation of important statistical assumptions or the mishandling of missing data. For data that involve whether an event occurs and when it occurs, the most appropriate statistical model are discrete time survival analysis models. However, until recently a method that uses discrete time multilevel survival analysis models and appropriately adjusts the standard errors to account for the nested structure of the data did not exist. The present study develops three models that combine discrete-time survival analysis and hierarchical linear modeling, to model Age of First Use of alcohol, and compares and contrasts these models with more commonly used OSL regression models. To illustrate the advantages of this method, the study evaluates the effects of several common covariates of alcohol use, such as Age of First Opportunity (AFO) of using alcohol, Family Attention (FA), Externalizing Behavior (EXT), Socioeconomic Status (SES), and Gender in a sample of 1785 youth from Caracas, Venezuela. Findings and Conclusions: Age of first opportunity of using alcohol appears to be the most influential variable in the models. The highest hazard rate of alcohol initiation was found at the first year of opportunity to use alcohol. The results obtained in this study varied across models depending on whether or not AFO was included in models as a covariate. When models did not control for AFO all other independent variables of this study become significant predictors of alcohol initiation in all models. Even though all models considered in the present study have their own advantages, discrete time multilevel survival analysis models are seen as the most appropriate in modeling age of first alcohol use. The main advantages of discrete time multilevel survival analysis models is in their ability to handle a particular kind of missing data called right censoring, such as youth who report delaying their initiation of alcohol use for all years covered in a given study. In investigating alcohol initiation, only about 18% reported no use of alcohol in this study, but when investigating illicit drugs, many more participants will be in a no-user group. For modeling early ages of drug initiation or any other event occurrence, when a vast majority of participants have not yet experienced it, discrete time survival analysis models should be used. |
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