Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/112616
|
| Title: | 應用多重插補法在包含遺漏資料的離散選擇模型
Applying Multiple Imputation to the Discrete Choice Model with Missing Data |
| Authors: | 簡廷翰
Jian, Ting Han |
| Contributors: | 鄭宗記
Cheng, Tsung Chi
簡廷翰
Jian, Ting Han |
| Keywords: | 多重差補法
離散選擇模型
Multiple imputation
Discrete choice model |
| Date: | 2017 |
| Issue Date: | 2017-09-13 14:11:41 (UTC+8) |
| Abstract: | 此篇文章探討，使用離散選擇模型(discrete choice model)中的邏輯模型(logit model)分析，若資料具有遺漏值(incomplete-data)，比較將具有遺漏值樣本值皆移除與使用多重插補方法補值之參數估計結果。
本文使用的多重差補法為Buuren(2007)等人所提出的Multiple Imputation by Chained Equation(MICE)多重插補方法進行補值，並使用Rubin(1987)所提出的方法合併參數估計結果。從模擬結果之參數偏誤盒狀圖可知插補後參數估計與設定參數差異不大，另外插補次數對於參數估計結果影響不大，且在遺漏比例(missing percentage)大時，參數估計結果比起將具有遺漏值樣本直接移除的參數估計較為穩定。
另外使用實際資料分析，發現具有遺漏值樣本直接移除的參數估標準差比起插補後參數估計標準差大的趨勢，與模擬結果相同。
This paper focuses on using discrete choice logit model to analyze incompleted data. To deal with the incompleted data, complete case analysis and multiple imputation are used, and compare the result of parameter estimates of the two methods.
The method of multiple imputation which this paper used is Multiple Imputation by Chained Equation (MICE). With the estimates from multiple imputed data sets, using Rubin’s method (1987) to pool the estimates. The simulation shows that after imputing the missing values, the estimates from the imputed data are not much difference from the real parameters. The number of imputation does not effect the estimates much. With larger missing percentage, the estimates from the imputed data is more robust than the estimates from the complete case analysis.
In real data analysis, the standard deviation of estimates from using complete case analysis are bigger than imputed data, this result is the same with the simulation. |
| Reference: | Atkinson, A. C. and T.-C. Cheng (2000). On Robust Linear Regression with Incomplete Data,
Computational Statistics and Data Analysis, 33, 361-380.
Azur, M. J., E. A. Stuart, C. Frangakis, and P. J. Leaf, (2011).Multiple Imputation by Chained Equations: What is it and how does it work?
International Journal of Methods in Psychiatric Research, 20(1), 40–49.
David A. Hensher, John M. Rose, William H. Greene (2015).Applied Choice Analysis,
CAMBRIDGE UNIVERSITY PRESS.
Gerko Vink, Laurence E. Frank, Jeroen Pannekoek, Stef van Buuren(2014).Predictive mean matching imputation of semicontinuous variables,
Statistica Neerlandica Vol. 68, nr. 1, pp. 61–90
Kenneth E. Train (2003), Discrete Choice Methods with Simulation,
CAMBRIDGE UNIVERSITY PRESS.
Kenneth E. Train, Yves Croissant, Kenneth Train’s exercises using the mlogit packages for R.
Also available at https://cran.r-project.org/web/packages/mlogit/vignettes/Exercises.pdf
James R. Carpenter and Michael G. Kenward (2013).Multiple Imputation and its application,
Wiley.
John W. Graham (2012).Missing Data-Analysis and Design,
Springer.
Jordan J. Louviere, David A. Hensher, Joffre D. Swait (2000).Stated Choice Methods-Analysis and Application,
CAMBRIDGE UNIVERSITY PRESS.
Peter C. Boxall and Wiktor L. Adamowicz (2002). Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach,
Environmental and Resource Economics 23: 421–446
Rubin, D.B. (1987). Multiple Imputation for Nonresponse in Surveys, New York :
John Wiley & Sons.
Rubin, D.B. (2002).Statistical Analysis with Missing Data Second Edition,
Wiley.
Van Buuren, S. and K. Groothuis-Oudshoorn (2011). mice: Multivariate Imputation by Chained Equations in R, Journal of Statistical Software, 45(3), 1-67.
Also available at http://www.jstatsoft.org/v45/i03/
Yves Croissant (2013).Estimation od multinomial logit model in R:The mlogit Packages .
Also available at https://cran.rproject.org/web/packages/mlogit/vignettes/mlogit.pdf |
| Description: | 碩士
國立政治大學
統計學系
104354001 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G1043540012 |
| Data Type: | thesis |
| Appears in Collections: | [統計學系] 學位論文
|
Files in This Item:
| File |
Size | Format | |
|---|
| 001201.pdf | 2210Kb | Adobe PDF2 | 37 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
