李丽霞,周舒冬,张敏,张岩波,郜艳晖.多水平模型和潜变量增长曲线模型在纵向数据分析中的应用及比较[J].Chinese journal of Epidemiology,2014,35(6):741-744 |
多水平模型和潜变量增长曲线模型在纵向数据分析中的应用及比较 |
Comparisons of two statistical approaches in studying the longitudinal data:the multilevel model and the latent growth curve model |
Received:October 30, 2013 |
DOI: |
KeyWord: 多水平模型 潜变量增长曲线模型 纵向数据 |
English Key Word: Multilevel model Latent growth curve model Longitudinal data |
FundProject:国家自然科学基金(30972553) |
Author Name | Affiliation | E-mail | Li Lixia | Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangdong Key Laboratory of Molecular Epidemiology, Guangzhou 510310, China | | Zhou Shudong | Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangdong Key Laboratory of Molecular Epidemiology, Guangzhou 510310, China | | Zhang Min | Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangdong Key Laboratory of Molecular Epidemiology, Guangzhou 510310, China | | Zhang Yanbo | Department of Epidemiology and Biostatistics, School of Public Health, Shanxi Medical University | | Gao Yanhui | Department of Epidemiology and Biostatistics, School of Public Health, Guangdong Pharmaceutical University, Guangdong Key Laboratory of Molecular Epidemiology, Guangzhou 510310, China | gao_yanhui@163.com |
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Abstract: |
比较多水平模型和潜变量增长曲线模型在纵向数据分析中的应用。文中以结直肠癌患者术后的生命质量情况为实例,比较两种方法的异同。结果表明两方法的参数估计值结果非常接近,多水平模型在模型构建时较为容易,而潜变量增长曲线模型在模型评价等方面具有优势。两方法均可很好地分析纵向观测的数据,且各有优点,研究者应根据需要选择合适的方法分析数据。 |
English Abstract: |
To compare two commonly used statistical approaches:the multilevel model and the latent growth curve model in analyzing longitudinal data. A longitudinal data set,obtained from the quality of life in patients with colorectal cancer after operation,was used to illustrate the similarities and differences between the two methods. Results from the study indicated that the latent growth curve modeling was equivalent to multilevel modeling with regards to longitudinal data which could yield identical results for the estimates of parameters. Multilevel model approach seemed easier for model specification. However,latent growth curve model had the advantage of providing model evaluation and was more flexible in statistical modeling by allowing the incorporation of latent variables. Both multilevel and latent growth curve models were suitable for analyzing longitudinal data with advantages on their own,they conld be chosen by researchers under different situation to be chosen accordingly by researchers under different situation. |
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