There continues to be a marked growth in the use of twin and family study methods to address issues in the genetic epidemiology of mental health. Examples include studies of anxiety and depression, addictive behaviors, vulnerability to stress, disorders of childhood and adolescence, and mental functioning in old age. The investment in data collection has generated a need for investigators to become skilled in the most powerful, efficient and up-to-date methods of data analysis and experimental design. These methods include structural equation modeling employing maximum likelihood estimation for univariate and multivariate genetic analyses, analyses of longitudinal data, analyses of gender differences, the treatment of categorical data, how to deal with ascertainment bias, the extension of twin methodology to extended pedigrees, the incorporation into twin and family studies of measured genotypes (QTL analysis), and analyses of experimental power. To meet this need we have developed an intensive computer based workshop on the methodology of twin and family studies. The first workshop was held in Leuven, Belgium, in 1987. Since 1990, with the support of NIMH, five workshops have been held in Boulder, CO, with a total enrollment of 226 trainees. The workshop resulted in the publication of a special edition of the journal Behavior Genetics on the genetic analysis of twin data and a textbook, Methodology for genetic studies of twins and families, based on the workshops and written by the faculty, has become the standard reference in the area. This proposal seeks funds to hold the Eleventh and successive annual International Workshops on the Methodology of Twin and Family Studies in Boulder, CO. So as to keep a balance between the needs of investigators being newly introduced to the methodology and more experienced researchers, we propose to alternate between an advanced workshop and an introductory workshop.
| Verhulst, Brad (2017) A Power Calculator for the Classical Twin Design. Behav Genet 47:255-261 |
| Maes, Hermine H M; Hatemi, Peter K; Neale, Michael C (2014) Lindon J. Eaves, Ph.D., M.A. (Oxon), D.Sc. Theory-model-data. Behav Genet 44:183-92 |
