Psychometric and Genetic Assessments of Substance Use

药物使用的心理测量和基因评估

• 批准号: 7936812
• 负责人: MICHAEL CHURTON NEALE
• 金额: $ 44.29万
• 依托单位: VIRGINIA COMMONWEALTH UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-30 至 2014-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7936812
• 关键词: Age; Alcohol or Other Drugs use; Behavior; Communities; Comorbidity; Computer software; Data; Data Analyses; Data Collection; Data Set; Dependence; Development; Diagnostic; Dimensions; Documentation; Drug abuse; Drug usage; Environmental Risk Factor; Epidemiology; Event; Factor Analysis; Genetic; Genetic Markers; Grant; Growth; Habits; Health; Household; Human Resources; Individual; Individual Differences; Instruction; Internet; Investigation; Joints; Knowledge; Life; Likelihood Functions; Measurement; Measures; Mental disorders; Methods; Modeling; Netherlands; Pattern; Performance; Phase; Phenotype; Predisposition; Probability; Property; Psychometrics; Publications; Quantitative Trait Loci; Randomized; Relapse; Relative (related person); Research; Research Design; Risk Factors; Running; S-1 Antimetabolite agent; Selection Criteria; Statistical Models; Subgroup; Surveys; Testing; Travel; Twin Studies; Virginia; Work; Writing; cohort; disorder risk; experience; flexibility; graduate student; instrument; interest; meetings; method development; model development; multimodality; novel; performance tests; response; simulation; symposium; theories; trait; uptake

PROJECT SUMMARY (See instructions): Dr. Flaherty and a graduate student RA will conduct statistical analyses using Mx, Latent Transition Analysis, R, and Stata. Project personnel will run simulation studies in order to test the performance of the latent class model under conditions with varying degrees of conformance with assumptions of the model. Project personnel will perform secondary data analysis testing the latent class model (and longitudinal extensions) performance as well as to add to our knowledge of substance use, abuse and dependence. The second project period will continue to investigate the interaction between model performance, measurement quality and item scale. The past four years' work have involved interesting problems with model selection and multimodality in the likelihood function, as well as statistical power to detect the proper number of classes. Measurement and covariate issues will also be studied in longitudinal models, including the latent transition and associative latent transition models. Dr. Flaherty will travel to Richmond to meet with Dr. Neale to work on the grant once a year. They will also have conference calls. All research will be written up and submitted for publication. Software and scripts produced will be made freely available to the public.

项目总结(见说明)： Flaherty博士和一名研究生RA将使用Mx，潜在转变分析，R， 还有斯塔塔。 项目人员将进行模拟研究，以测试潜在班级模型在 与模型的假设具有不同程度一致性的条件。 项目人员将对潜在班级模型(和纵向模型)进行二次数据分析 性能，以及增加我们对药物使用、滥用和依赖的知识。 第二个项目期将继续调查模型性能之间的相互作用， 测量质量和项目规模。过去四年的工作涉及到与模型有关的有趣问题 在似然函数中的选择和多模，以及检测适当数目的统计功率 上课。还将在纵向模型中研究测量和协变量问题，包括潜在的 相变和相联潜在相变模型。 弗莱厄蒂博士将每年前往里士满与尼尔博士会面一次，为这项拨款工作。他们还将拥有 电话会议。 所有的研究都将被写下来并提交出版。 制作的软件和脚本将免费提供给公众。