本次给大家讲一下stataNMA的作图过程的贡献图。需要的变量主要是 t1 t2 logor selogor,在stata中普通的metan命令处理后就得到这样的数据。
use "F:\【Network Meta-Analysis - 网状meta分析】使用STATA软件绘图\example_datasets\coronary artery disease pairwise.dta"
//netweight lnOR selnOR t1 t2
//本例采用 logOR
netweight logOR selogOR t1 t2
//结果如下
Direct comparisons and number of included studies:
Indirect comparisons:
Direct relative effects:
c1
r1 -0.080
r2 -0.041
r3 -0.087
r4 0.165
Variances of direct relative effects:
c1 c2 c3 c4
r1 .0425 0 0 0
r2 0 .0123 0 0
r3 0 0 .027 0
r4 0 0 0 .0253
Note: Effect sizes of 36 observations were reversed (stored in matrix e(R))
Basic contrasts:
BMSvsDES BMSvsMT BMSvsPTCA
Design matrix:
c1 c2 c3
r1 1 0 0
r2 0 1 0
r3 0 0 1
r4 0 -1 1
r5 -1 1 0
r6 -1 0 1
Contribution of each direct comparison in each pairwise summary effect:
r1 r2 r3 r4
r1 1.000 0.000 0.000 0.000
r2 0.000 0.810 0.190 -0.190
r3 0.000 0.418 0.582 0.418
r4 0.000 -0.392 0.392 0.608
r5 -1.000 0.810 0.190 -0.190
r6 -1.000 0.418 0.582 0.418
Percentage contribution of each direct comparison in each pairwise summary effect:
_P1 _P2 _P3 _P4
comp1 100.0 0.0 0.0 0.0
comp2 0.0 68.0 16.0 16.0
comp3 0.0 29.5 41.0 29.5
comp4 0.0 28.1 28.1 43.7
comp5 45.7 37.0 8.7 8.7
comp6 41.4 17.3 24.1 17.3
Percentage contribution of each direct comparison in the entire network:
_C1 _C2 _C3 _C4
network 31.2 29.6 20.2 19.0
//图形如下
Figure 3. Contribution plot for the coronary artery disease network. The size of each square is proportional to the weight attached to each
direct summary effect (horizontal axis) for the estimation of each network summary effects (vertical axis). The numbers re-express the weights as
percentages. (MT = medical therapy, PTCA = percutaneous transluminal balloon coronary angioplasty, BMS = bare-metal stents, DES = drug-eluting
stents).
//图形解释
图3。冠状动脉疾病网络贡献图。每方的大小 代表权重,与直接总结效果(横轴)估计的每个网络总结效果(垂直轴) 成正比。数字重新表达权重,用
百分比。(mt=医学治疗,PCTA =冠状血管成形术,BMS =裸金属支架,DES =药物洗脱支架)。
横轴:直接总结结果—直接比较
垂直轴:每个网络总结效果(垂直轴)—网状比较
从左上到右下方向看。
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