Implementation of Network Meta-Analysis with nlme Package in R Software_Chinese Journal of Evidence-Based Medicine

Authors：

 ZHANGChao ¹ ,  NIUYu-ming ² , ZENGXian-tao ^1,2

1. Center for Evidence-Based Medicine and Clinical Research, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China;
2. Department of Stomatology, Taihe Hospital, Hubei University of Medicine, Shiyan 442000, China;

Corresponding author：

NIUYu-ming, Email: zengxiantao1128@163.com

Keywords：

Network meta-analysis; Generalized linear mixed model; R language; nlme package

DOI：

10.7507/1672-2531.20140060

Video：

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The nlme package is developed based on the generalized least squares (gls) and linear mixed-effects model (lme). It can perform meta-analysis based on linear and nonlinear mixed effects models in R language. When conducting meta-analysis using nlme package in R language, the first step is to translate the data into its logarithm estimation. In this article, we introduce how to perform network meta-analysis using R language nlme package and show the core step of data translation in detail.

Citation： ZHANGChao, NIUYu-ming, ZENGXian-tao. Implementation of Network Meta-Analysis with nlme Package in R Software. Chinese Journal of Evidence-Based Medicine, 2014, 14(3): 355-360. doi: 10.7507/1672-2531.20140060 Copy

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2.	林毓玲(译).广义线性模型.上海:格致出版社, 2011.
3.	Pinheiro JC, Bates DM. Mixed-Effects Models in S and S-PLUS. USA, Ney Work:Springer, 2000.
4.	Tornøe CW, Agersø H, Jonsson EN, et al. Non-linear mixed-effects pharmacokinetic/pharmacodynamic modelling in NLME using differential equations. Comput Methods Programs Biomed, 2004, 76(1):31-40.
5.	Zeileis A, Kleiber C, Jackman S. Regression models for count data in R. Available in ePubWU:April 2007. Available at:http://epub.wu.ac.at/1168/.
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7.	张天嵩, 熊茜.网络Meta分析在R软件中的实现.循证医学, 2012, 12(3):185-188.
8.	曾宪涛, 张超, 郭毅. R软件R2WinBUGS程序包在网状Meta分析中的应用.中国循证医学杂志, 2013, 13(9):1137-1144.
9.	Jonas DE, Wilkins TM, Bangdiwala S, et al. Findings of Bayesian Mixed Treatment Comparison Meta-Analyses:Comparison and Exploration Using Real-World Trial Data and Simulation[Internet]. Rockville(MD):Agency for Healthcare Research and Quality(US);.
10.	Feb. Appendix A, WinBUGS Code Used in Bayesian Mixed Treatment Comparisons Meta-Analysis. Available at:http://www.ncbi.nlm.nih.gov/books/NBK126104/.
11.	董圣杰, 曾宪涛, 郭毅. R软件Metafor程序包在Meta分析中的应用.中国循证医学杂志, 2012, 12(9):1141-1147.
12.	张超, 董圣杰, 曾宪涛. R软件gemtc程序包在网状Meta分析中的应用.中国循证医学杂志, 2013, 13(10):1258-1264.
13.	张超, 徐畅, 曾宪涛.网状Meta分析中网状关系图的绘制.中国循证医学杂志, 2013, 13(11):1382-1386.

1. Dunteman GH, Ho MHR. An introduction to generalized linear models. Thousand Oaks, CA:Sage Publications, 2006.
2. 林毓玲(译).广义线性模型.上海:格致出版社, 2011.
3. Pinheiro JC, Bates DM. Mixed-Effects Models in S and S-PLUS. USA, Ney Work:Springer, 2000.
4. Tornøe CW, Agersø H, Jonsson EN, et al. Non-linear mixed-effects pharmacokinetic/pharmacodynamic modelling in NLME using differential equations. Comput Methods Programs Biomed, 2004, 76(1):31-40.
5. Zeileis A, Kleiber C, Jackman S. Regression models for count data in R. Available in ePubWU:April 2007. Available at:http://epub.wu.ac.at/1168/.
6. Pinheiro J, Bates D, DebRoy S, et al. nlme:Linear and Nonlinear Mixed Effects Models. Version 3.1, 2013. Available at:http://cran.rproject.org/web/packages/nlme/nlme.pdf.
7. 张天嵩, 熊茜.网络Meta分析在R软件中的实现.循证医学, 2012, 12(3):185-188.
8. 曾宪涛, 张超, 郭毅. R软件R2WinBUGS程序包在网状Meta分析中的应用.中国循证医学杂志, 2013, 13(9):1137-1144.
9. Jonas DE, Wilkins TM, Bangdiwala S, et al. Findings of Bayesian Mixed Treatment Comparison Meta-Analyses:Comparison and Exploration Using Real-World Trial Data and Simulation[Internet]. Rockville(MD):Agency for Healthcare Research and Quality(US);.
10. Feb. Appendix A, WinBUGS Code Used in Bayesian Mixed Treatment Comparisons Meta-Analysis. Available at:http://www.ncbi.nlm.nih.gov/books/NBK126104/.
11. 董圣杰, 曾宪涛, 郭毅. R软件Metafor程序包在Meta分析中的应用.中国循证医学杂志, 2012, 12(9):1141-1147.
12. 张超, 董圣杰, 曾宪涛. R软件gemtc程序包在网状Meta分析中的应用.中国循证医学杂志, 2013, 13(10):1258-1264.
13. 张超, 徐畅, 曾宪涛.网状Meta分析中网状关系图的绘制.中国循证医学杂志, 2013, 13(11):1382-1386.

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Implementation of Network Meta-Analysis with nlme Package in R Software

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