Statistical modeling plays a central role in a wide range of scientific investigations. Studies of complex traits and disorders such as addictive behaviors, psychopathology, cardiovascular disease, obesity, and cancer are now faced with a set of statistical challenges that require improved software. The challenges include: i) the difficulty of measuring behavioral traits;ii) the availability of technologies - such as magnetic resonance imaging, continuous physiological monitoring and microarrays - which generate extremely large amounts of data often with complex time-dependent patterning, and iii) increased sophistication in the statistical models used to analyze the data. The current project proposes to rewrite the popular Mx statistical package in order to address these challenges. Both the user specification of models and the algorithms used to ?t them will be significantly improved. The software will be i) split into modules that interoperate with the R statistical package, ii) released as open source so as to provide a stable path for future maintenance and development and iii) integrated with the VDL parallel work software. Grid/parallel computing and data management using VDL will provide significant speedup for processing large (up to multi-terabyte) data sets, through the use of analytical work that provide detailed provenance tracking and annotation of derived results. Revised algorithms for model and optimization will increase both the scope of the software and its performance. Both the code and its use will be documented and disseminated at national and international workshops. Studies of complex traits and disorders such as addictive behaviors, psychopathology, cardiovascular disease, obesity, and cancer are now faced with a set of statistical challenges that require improved software. The challenges include: i) the difficulty of measuring behavioral traits;ii) the availability of technologies - such as magnetic resonance imaging, continuous physiological monitoring and microarrays - which generate extremely large amounts of data often with complex time-dependent patterning;and iii) increased sophistication in the statistical models used to analyze the data. The current project proposes to develop software that uses massively parallel computing grids, """"""""cyberinfrastructure"""""""", in order to address these challenges.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DA024304-03
Application #
7666926
Study Section
Special Emphasis Panel (ZDA1-GXM-A (27))
Program Officer
Onken, Lisa
Project Start
2007-09-26
Project End
2011-07-31
Budget Start
2009-08-01
Budget End
2010-07-31
Support Year
3
Fiscal Year
2009
Total Cost
$269,300
Indirect Cost
Name
University of Virginia
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
065391526
City
Charlottesville
State
VA
Country
United States
Zip Code
22904
Maes, Hermine H; Morley, Kate; Neale, Michael C et al. (2018) Cross-Cultural Comparison of Genetic and Cultural Transmission of Smoking Initiation Using an Extended Twin Kinship Model. Twin Res Hum Genet 21:179-190
Boker, Steven M; Martin, Mike (2018) A Conversation between Theory, Methods, and Data. Multivariate Behav Res :1-14
Maes, Hermine H; Neale, Michael C; Ohlsson, Henrik et al. (2016) A Bivariate Genetic Analysis of Drug Abuse Ascertained Through Medical and Criminal Registries in Swedish Twins, Siblings and Half-Siblings. Behav Genet 46:735-741
Boker, Steven; Neale, Michael; Maes, Hermine et al. (2011) OpenMx: An Open Source Extended Structural Equation Modeling Framework. Psychometrika 76:306-317
Maes, Hermine H; Neale, Michael C; Chen, Xiangning et al. (2011) A twin association study of nicotine dependence with markers in the CHRNA3 and CHRNA5 genes. Behav Genet 41:680-90
von Oertzen, Timo; Boker, Steven M (2010) Time Delay Embedding Increases Estimation Precision of Models of Intraindividual Variability. Psychometrika 75:158-175
Boker, Steven M; Molenaar, Peter C M; Nesselroade, John R (2009) Issues in intraindividual variability: individual differences in equilibria and dynamics over multiple time scales. Psychol Aging 24:858-62