課程資訊
課程名稱
應用線性混合效應模式
Applied Linear Mixed-Effects Modeling 
開課學期
111-1 
授課對象
生物資源暨農學院  森林環境暨資源學系  
授課教師
林增毅 
課號
Forest5077 
課程識別碼
625EU2310 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期二2,3,4(9:10~12:10) 
上課地點
林五 
備註
初選不開放。本課程以英語授課。修習本課程須經授課教師同意。
總人數上限:1人 
 
課程簡介影片
 
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課程概述

Linear mixed-effects modeling is necessary when analyzing grouped data that are particularly common in forestry. Sampling designs in forestry are often hierarchical in nature such as in large-scale field blocked experiments and multistage forest inventory. Other grouped data that are often encountered in forestry are longitudinal data and repeated measures such as forest growth and yield data. It is important for modeling and analysis to properly account for correlation presented in grouped data so that interpretation of results is valid. This course will introduces theory of linear mixed-effects modeling and focuses on its application particularly using examples of hierarchical datasets with autocorrelation. An emphasis will be placed on the process of model-building including examining spatial and temporal autocorrelation and weighting. The course will be taught in English. 

課程目標
The course will introduce various aspects of mixed-effects modeling starting from introduction to regression theory and then moves to linear mixed effects models. The course will go in depth on autocorrelation and weighting based on the theory of Generalized Least Square. Finally, the course will introduce Generalized Linear Models and its mixed-effects approach. By the end of the course, students should be comfortable in identifying nested structures in the data and construct appropriate model structures. 
課程要求
Basic applied and mathematical statistics and R language 
預期每週課後學習時數
 
Office Hours
另約時間 
參考書目
1. Venables, W.N., Ripley, B.D., 2002. Modern Applied Statistics with S, 4th ed, Statistics and Computing. Springer-Verlag New York, New York, NY, USA.
2. Robinson AP, Hamann JD. 2011. Forest Analytics with R. 1st Ed. Springer. Dordrecht, Germany.
 
指定閱讀
1. Pinheiro, J.C., Bates, D.M., 2000. Mixed-Effects Models in S and S-PLUS, 1st ed, Statistics and Computing. Springer-Verlag New York, New York, NY, USA.
2. Gelman, A., Hill, J., 2006. Data Analysis Using Regression and Multilevel/Hierarchical Models, 1st ed. Cambridge University Press, Cambridge, UK. 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
無資料