Using SAS program to frame meta-analysis of longitudinal data based on multi-level model_Chinese Journal of Evidence-Based Medicine

Authors：

XIAO Lihua ¹ , ZHENG Jianqing ¹ ,  HUANG Bifen ² , SU Jingjing ¹ , WU Min ¹

1. The Second Affiliated Hospital of Fujian Medical University, Quanzhou, 362000, P.R.China;
2. Affiliated People’s Hospital of Quanzhou Medical College , Quanzhou, 362000, P.R.China;

Corresponding author：

HUANG Bifen, Email: 18060108268@180.cn

Keywords：

Multilevel models; Linear regression; Longitudinal data; Meta-analysis; SAS macros

DOI：

10.7507/1672-2531.201810044

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Longitudinal data had intrinsic correlation problems at different time points, and traditional meta-analysis techniques cannot resolve this problem. Regression coefficients based on multi-level models can fully consider the correlations of longitudinal data at various time points. This paper uses SAS software to perform multi-level regression coefficient model meta-analysis and provides programming code which is simple and easy to operate.

Citation： XIAO Lihua, ZHENG Jianqing, HUANG Bifen, SU Jingjing, WU Min. Using SAS program to frame meta-analysis of longitudinal data based on multi-level model. Chinese Journal of Evidence-Based Medicine, 2019, 19(5): 614-621. doi: 10.7507/1672-2531.201810044 Copy

1.	Jackson D, Rollins K, Coughlin P. A multivariate model for the meta-analysis of study level survival data at multiple times. Res Synth Methods, 2014, 5(3): 264-272.
2.	Arends LR, Hunink MG, Stijnen T. Meta-analysis of summary survival curve data. Stat Med, 2008, 27(22): 4381-4396.
3.	Ishak KJ, Platt RW, Joseph L, et al. Meta-analysis of longitudinal studies. Clin Trials, 2007, 4(5): 525-539.
4.	Connis RT, Evans RL, Hendricks RD. Meta-analysis with longitudinal studies: controlling for analytical bias. Psychol Rep, 1996, 79(3 Pt 2): 1383-1386.
5.	Lopes HF, Müller P, Rosner GL. Bayesian meta-analysis for longitudinal data models using multivariate mixture priors. Biometrics, 2003, 59(1): 66-75.
6.	Maas CJM, Hox JJ, Lensvelt-Mulders GJLM. Longitudinal Meta-analysis. Quality Quantity, 2004, 38(4): 381-389.
7.	Idris NRN. Modelling repeated measures data in meta-analysis: an alternative approach. Available at: http://irep.iium.edu.my/5552/1/SKSM16.pdf.
8.	张天嵩, 董圣杰, 周支瑞. 高级 Meta 分析方法—基于 Stata 实现. 上海: 复旦大学出版社, 2015.
9.	Tan A, Liao C, Mo Z, et al. Meta-analysis of holmium laser enucleation versus transurethral resection of the prostate for symptomatic prostatic obstruction. Br J Surg, 2007, 94(10): 1201-1208.
10.	Jackson D, White IR, Riley RD. A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression. Biom J, 2013, 55(2): 231-245.

1. Jackson D, Rollins K, Coughlin P. A multivariate model for the meta-analysis of study level survival data at multiple times. Res Synth Methods, 2014, 5(3): 264-272.
2. Arends LR, Hunink MG, Stijnen T. Meta-analysis of summary survival curve data. Stat Med, 2008, 27(22): 4381-4396.
3. Ishak KJ, Platt RW, Joseph L, et al. Meta-analysis of longitudinal studies. Clin Trials, 2007, 4(5): 525-539.
4. Connis RT, Evans RL, Hendricks RD. Meta-analysis with longitudinal studies: controlling for analytical bias. Psychol Rep, 1996, 79(3 Pt 2): 1383-1386.
5. Lopes HF, Müller P, Rosner GL. Bayesian meta-analysis for longitudinal data models using multivariate mixture priors. Biometrics, 2003, 59(1): 66-75.
6. Maas CJM, Hox JJ, Lensvelt-Mulders GJLM. Longitudinal Meta-analysis. Quality Quantity, 2004, 38(4): 381-389.
7. Idris NRN. Modelling repeated measures data in meta-analysis: an alternative approach. Available at: http://irep.iium.edu.my/5552/1/SKSM16.pdf.
8. 张天嵩, 董圣杰, 周支瑞. 高级 Meta 分析方法—基于 Stata 实现. 上海: 复旦大学出版社, 2015.
9. Tan A, Liao C, Mo Z, et al. Meta-analysis of holmium laser enucleation versus transurethral resection of the prostate for symptomatic prostatic obstruction. Br J Surg, 2007, 94(10): 1201-1208.
10. Jackson D, White IR, Riley RD. A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression. Biom J, 2013, 55(2): 231-245.

Chinese Journal of Evidence-Based Medicine

Using SAS program to frame meta-analysis of longitudinal data based on multi-level model

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content