Statistical Models of NP Functioning for MH Services

超出提供的空间。为精神卫生服务研究提供准确和精确的认知缺陷信息的神经心理学(NP)评估的统计分析新方法正在被提出。从NP数据集中提取更丰富和更精确的认知信息的潜在好处是非常显著的：这种分析方法有可能(1)揭示NP缺陷和残疾之间的特定关系；(2)增强我们选择针对特定认知缺陷的治疗和康复方法的能力；(3)提高我们检测治疗反应的敏感度，并检测不同临床组之间认知加工的差异；以及(4)通过序贯测试节省临床评估时间和评估成本。提出的分析方法包括序贯测试技术，可以大大缩短NP评估测试的长度。该项目具有潜在的广泛适用性。当对测量认知功能感兴趣时，这些技术和模型可以用于其他临床应用。表演网站========================================Section End===========================================

EXCEED THE SPACE PROVIDED. New methods for statistical analysis ofneuropsychological (NP) assessments for mental health services research are being proposed which can provide accurate and precise information about cognitive deficits. The potential benefits of extracting richer and more precise cognitive information from NP data sets are very significant: This analytic approach has the potential to (1) unveil specific relationships between NP deficits and disability; (2) enhance our ability to select treatment and rehabilitative methods that target specific cognitive deficiencies; (3) enhance our sensitivity to detect treatment responses, and to detect differences in cognitive processing between different clinical groups; and (4) save clinical assessment time and assessment costs through sequential testing. The proposed analytic approach includes sequential testing techniques that can drastically shorten the length of NP assessment testing. This project has potentially broad applicability. The techniques and models can be used in other clinical applications when it is of interest to measure cognitive functioning. PERFORMANCE SITE ========================================Section End===========================================