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Linear Mixed Models for Longitudinal Data with Nonrandom Dropouts

並列摘要


Longitudinal studies represent one of the principal research strategies employed in medical and social research. These studies are the most appropriate for studying individual change over time. The prematurely withdrawal of some subjects from the study (dropout) is termed nonrandom when the probability of missingness depends on the missing value. Nonrandom dropout is common phenomenon associated with longitudinal data and it complicates statistical inference. Linear mixed effects model is used to fit longitudinal data in the presence of nonrandom dropout. The stochastic EM algorithm is developed to obtain the model parameter estimates. Also, parameter estimates of the dropout model have been obtained. Standard errors of estimates have been calculated using the developed Monte Carlo method. All these methods are applied to two data sets.

並列關鍵字

Dropout longitudinal data mixed models stochastic EM

被引用紀錄


Juyn, Y. F. (2015). β-Ti-28Nb-11Ta-8Zr 合金之陽極氧化表面改質添加SrHA及其生物活性研究 [master's thesis, National Tsing Hua University]. Airiti Library. https://doi.org/10.6843/NTHU.2015.00217
Kuo, Y. M. (2013). 陽極處理具骨相容彈性模數之β型鈦鈮鉭鋯植體及其宿主細胞與抗菌能力之揭露 [master's thesis, National Tsing Hua University]. Airiti Library. https://doi.org/10.6843/NTHU.2013.00808
Ng, S. L. (2017). 實用商業詞彙之流行度搜索與世界競爭力關係 [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU201700898
Wang, R. Y. (2011). 平衡資料結構下隨機效應變異數分析模型之無偏風險估計 [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2011.10939
李怡君(2006)。交叉路口交通量預測模式之研究〔碩士論文,國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2006.02579

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