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