Question

我有兴趣结合70岁时心脏病的生存估计。由于这些是生存估计，因此它们的范围从0到1（与比例相似）。我进行了5项研究，估算摘要，95％CI，n和SE如下所示。每行代表一个研究。

> dat
  Estimate Lower Upper   n       SE
1     0.55  0.40  0.71 100 1.479592
2     0.23  0.15  0.35 300 2.562728
3     0.54  0.44  0.66 200 2.092459
4     0.59  0.30  0.75 400 2.959184
5     0.88  0.67  0.98  40 0.935776

dat <- structure(list(Estimate = c(0.55, 0.23, 0.54, 0.59, 0.88), Lower = c(0.4, 
0.15, 0.44, 0.3, 0.67), Upper = c(0.71, 0.35, 0.66, 0.75, 0.98
), n = c(100, 300, 200, 400, 40), SE = c(1.47959183673469, 2.56272823568864, 
2.09245884228672, 2.95918367346939, 0.935776042294725)), .Names = c("Estimate", 
"Lower", "Upper", "n", "SE"), row.names = c(NA, -5L), class = "data.frame")

软件包rma中的

metafor允许我输入sei（标准错误），该数据将封装根据研究得出的来自95％CI的信息，但会产生可信度间隔不介于0和1之间（即CI为-0.51、1.77）。我该如何限制呢？即确保rma将我的dat$Estimate视为0到1之间的值。

> rma(dat$Estimate, dat$SE, method = "DL")

Random-Effects Model (k = 5; tau^2 estimator: DL)

tau^2 (estimated amount of total heterogeneity): 0 (SE = 1.2621)
tau (square root of estimated tau^2 value):      0
I^2 (total heterogeneity / total variability):   0.00%
H^2 (total variability / sampling variability):  1.00

Test for Heterogeneity: 
Q(df = 4) = 0.1380, p-val = 0.9977

Model Results:

estimate      se    zval    pval    ci.lb   ci.ub   
  0.6302  0.5822  1.0824  0.2791  -0.5109  1.7712   

---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

R：metafor的rma，用于组合0到1之间的值

0 个答案: