Biomaterial Database

The relation between adolescent alcohol use and peer alcohol use: a longitudinal random coefficients model. 1997

P J Curran, and E Stice, and L Chassin

Department of Psychology, Duke University, Durham, North Carolina 27708-0085, USA. curran@duke.edu

Longitudinal latent growth models were used to examine the relation between changes in adolescent alcohol use and changes in peer alcohol use over a 3-year period in a community-based sample of 363 Hispanic and Caucasian adolescents. Both adolescent alcohol use and peer alcohol use were characterized by positive linear growth over time. Not only were changes in adolescent alcohol use closely related to changes in peer alcohol use, but the initial status on peer alcohol use was predictive of later increases in adolescent alcohol use and the initial status on adolescent alcohol use was predictive of later increases in peer alcohol use. These results are inconsistent with models positing solely unidirectional effects between adolescent alcohol use and peer alcohol use.

UI	MeSH Term	Description	Entries
D008297	Male		Males
D008960	Models, Psychological	Theoretical representations that simulate psychological processes and/or social processes. These include the use of mathematical equations, computers, and other electronic equipment.	Model, Mental,Model, Psychological,Models, Mental,Models, Psychologic,Psychological Models,Mental Model,Mental Models,Model, Psychologic,Psychologic Model,Psychologic Models,Psychological Model
D010379	Peer Group	Group composed of associates of same species, approximately the same age, and usually of similar rank or social status.	Group, Peer,Groups, Peer,Peer Groups
D010553	Personality Development	Growth of habitual patterns of behavior in childhood and adolescence.	Development, Personality
D011446	Prospective Studies	Observation of a population for a sufficient number of persons over a sufficient number of years to generate incidence or mortality rates subsequent to the selection of the study group.	Prospective Study,Studies, Prospective,Study, Prospective
D012044	Regression Analysis	Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable.	Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002648	Child	A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL.	Children
D003430	Cross-Sectional Studies	Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time.	Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D005163	Factor Analysis, Statistical	A set of statistical methods for analyzing the correlations among several variables in order to estimate the number of fundamental dimensions that underlie the observed data and to describe and measure those dimensions. It is used frequently in the development of scoring systems for rating scales and questionnaires.	Analysis, Factor,Analysis, Statistical Factor,Factor Analysis,Statistical Factor Analysis,Analyses, Factor,Analyses, Statistical Factor,Factor Analyses,Factor Analyses, Statistical,Statistical Factor Analyses
D005260	Female		Females