QUANTITATIVE TRAINING FOR MENTAL HEALTH RESEARCH

心理健康研究通常需要考虑先进的统计和心理测量方法，以调整混淆和测量误差，并在非实验背景下对因果过程进行建模。虽然许多新兴的方法是由统计学家和生物统计学家开发的，但这些方法的应用往往落在心理学系受过训练的人的肩上。为了培养一支能够从定量方法的进步中受益的心理健康研究骨干队伍，我们建议在纽约大学心理学系继续开展心理健康研究的定量培训项目。该项目为两名博士后和五名预科研究员提供心理测量学、统计学和研究设计方面的具体、复杂的培训。该培训借鉴了纽约大学统计与运筹学系以及心理学系的课程。除了向心理健康研究人员提供定量方法方面的具体指导外，培训计划旨在影响心理健康研究人员定量方法的更广泛背景，培训计划旨在影响心理学系的更广泛背景。研究员参与正在进行的研究项目，涉及纽约大学临床、社区、认知和发展心理学中的心理健康变量，以及纽约地区的研究环境。他们在逻辑回归、随机回归模型和多元技术等方法方面的专业知识，使教师和其他学生能够更好地了解目前可用于心理健康研究的统计方法。研究员对精神病学流行病学和公共卫生领域的重要问题的接触可能会导致基础生理科学家更多地参与这些领域。

Mental health research often requires the consideration of advanced statistical and psychometric methods to adjust for confounding and measurement error, and to model causal processes in non-experimental contexts. Although many of the emerging methods are developed by statisticians and biostatisticians, the application of these methods often falls on the shoulders of persons trained in psychology departments. In order to develop a cadre of mental health researchers who are well equipped to benefit from advances in quantitative methods, we propose to continue operating a quantitative training program in mental health research at the Department of Psychology at NYU. The program provides specific, sophisticated training in psychometrics, statistics and study design to two postdoctoral fellows and five predoctoral fellows. The training draws on the curriculum of NYU's Department of Statistics and Operations Research as well as of the Department of Psychology. In addition to providing specific instruction in quantitative methods to mental health researchers, the training program aims to affect the broader context of the quantitative methods to mental health researchers, the training program aims to affect the broader context of the Psychology Department. Fellows participate in ongoing research projects that involve mental health variables in clinical, community, cognitive and developmental psychology at NYU, as well as in research settings in the New York area. Their expertise in methods such as logistic regression, random regression models and multivariate techniques allow faculty and other students to appreciate better the statistical methodology that is now available for mental health research. Fellows' exposure to important issues in psychiatric epidemiology and public health may lead to more involvement by basic physiological scientists in these areas.