Department of Rehabilitation Services, Texas Tech University Health Sciences Center, Lubbock, TX, USA.
Am J Phys Med Rehabil. 2013 Apr;92(4):343-50. doi: 10.1097/PHM.0b013e318278b1df.
The aims of this study were to conduct an exploratory factor analysis on admission data, identify key variables that may predict discharge to home, and create and test a predictor model using confirmatory factor analysis and structured equation modeling.
A secondary data analysis was conducted using a data set of 176,419 cases. Statistical analyses used included an exploratory factor analysis, confirmatory factor analysis, and structural equation modeling using variables collected upon admission.
The hypothesis model included ten items that loaded on a latent factor of physical performance and five items that loaded on a latent factor of cognitive performance. The final predictor model resulted in three physical performance items (grooming, toileting, and chair transfers) and four cognitive performance items (comprehension, expression, problem solving, and memory) with results of χ(2) (df) of 44,708.630 (11), root mean square error of approximation of 0.152, and comparative fit index/Tucker-Lewis index of 0.957/0.918.
Four factors (admit cognitive scores, admit physical scores, age, and diagnosis category) were identified and tested. The latent factors admit cognitive performance scores and admit physical performance scores were shown to be strong predictors for discharge to home, whereas diagnosis categories and age were weak predictors in this model.
本研究旨在对入院数据进行探索性因子分析，确定可能预测出院回家的关键变量，并使用验证性因子分析和结构方程建模创建和测试预测模型。
使用 176419 例病例的数据集进行二次数据分析。使用入院时收集的变量进行的统计分析包括探索性因子分析、验证性因子分析和结构方程建模。
假设模型包括 10 个项目，这些项目加载在身体表现的潜在因素上，5 个项目加载在认知表现的潜在因素上。最终的预测模型产生了 3 个身体表现项目（修饰、如厕和椅子转移）和 4 个认知表现项目（理解、表达、解决问题和记忆），结果为 χ(2)（df）为 44708.630（11），近似均方根误差为 0.152，拟合优度指数/塔克-刘易斯指数为 0.957/0.918。
确定并测试了四个因素（入院认知评分、入院身体评分、年龄和诊断类别）。潜在的认知表现得分和身体表现得分表明是出院回家的有力预测因素，而诊断类别和年龄在该模型中是较弱的预测因素。
