The proposed ISA research has three major aims: to develop new statistical methods to better answer substantive questions in alcohol research related to the development and prevention of alcohol problems, to collaborate with alcohol researchers on advanced statistical analysis of their data, and to disseminate information on the new methods so that others in the alcohol and related fields can benefit from them. Five areas of statistics integral to the study of the development and prevention of alcohol problems will be studied: categorical and other non-normal data analysis, mixture data analysis, multilevel data analysis, missing data analysis, and longitudinal data analysis. Collaboration with researchers on the analysis of their alcohol data will involve advanced analyses of several longitudinal datasets concerned with alcohol problems. Dissemination of information on the new methods developed within the project will take place through the publication of substantively- and methodologically-oriented articles, the writing of a book, and training sessions describing these new advances. Two major types of career development and training activities are planned within the ISA: training on substantive research issues related to the development and prevention of alcohol problems and advanced statistical training. The central part of the substantive training will occur through apprentice-like relationships with a few key alcohol experts. This will be complemented by relevant substantive and statistical courses and attendance at professional meetings. REVIEW A

National Institute of Health (NIH)
National Institute on Alcohol Abuse and Alcoholism (NIAAA)
Research Scientist Development Award - Research (K02)
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Study Section
Clinical and Treatment Subcommittee (ALCP)
Program Officer
Yahr, Harold
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University of California Los Angeles
Schools of Nursing
Los Angeles
United States
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Brown, C Hendricks; Wang, Wei; Kellam, Sheppard G et al. (2008) Methods for testing theory and evaluating impact in randomized field trials: intent-to-treat analyses for integrating the perspectives of person, place, and time. Drug Alcohol Depend 95 Suppl 1:S74-S104
Boomsma, Dorret I; Cacioppo, John T; Muthen, Bengt et al. (2007) Longitudinal genetic analysis for loneliness in Dutch twins. Twin Res Hum Genet 10:267-73
Muthen, Bengt (2006) Should substance use disorders be considered as categorical or dimensional? Addiction 101 Suppl 1:6-16
Muthen, Bengt; Asparouhov, Tihomir (2006) Item response mixture modeling: application to tobacco dependence criteria. Addict Behav 31:1050-66
Muthen, Bengt; Asparouhov, Tihomir; Rebollo, Irene (2006) Advances in behavioral genetics modeling using Mplus: applications of factor mixture modeling to twin data. Twin Res Hum Genet 9:313-24
Larsen, Klaus (2005) The cox proportional hazards model with a continuous latent variable measured by multiple binary indicators. Biometrics 61:1049-55
Lubke, Gitta H; Muthen, Bengt (2005) Investigating population heterogeneity with factor mixture models. Psychol Methods 10:21-39
Larsen, Klaus (2004) Joint analysis of time-to-event and multiple binary indicators of latent classes. Biometrics 60:85-92
Muthen, Bengt (2003) Statistical and substantive checking in growth mixture modeling: comment on Bauer and Curran (2003). Psychol Methods 8:369-77; discussion 384-93
Harford, Thomas C; Wechsler, Henry; Muthen, Bengt O (2003) Alcohol-related aggression and drinking at off-campus parties and bars: a national study of current drinkers in college. J Stud Alcohol 64:704-11

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