我意识到我可以使用这个例子 http://gforge.se/2013/12/the-forestplot-of-dreams/ 制作两个单独的数据集,一个用于调整值,一个用于匹配值,然后组合 - 但不必再次输入所有值。
我想你提到的链接(或 这个 )是最佳解决方案。 您不必键入所有数据 - 只需在数据框中添加一个额外的列,然后对其进行子集化。您可以像这样添加列:
type = c(NA, NA, NA, "adjusted", "matched","adjusted", "matched", NA, "adjusted", "matched","adjusted", "matched", NA, "adjusted", "matched","adjusted", "matched", "adjusted", "matched")
所以你的数据框将如下所示:
main_acevccb <- structure(list( mean = c(NA, NA, NA, -1.12, -0.64, -1.55,-1.60, NA, -1.35,-1.44, -1.3, -1.2, NA, -1.29,-1.23, -2.82,-2.15, -1.84,-2.72), lower = c(NA, NA, NA, -1.41, -0.84, -1.85, -1.86, NA, -1.71,-1.9, -1.57,-1.52, NA, -1.53, -1.54, -4.04, -3.61, -2.85,-4.45), upper = c(NA, NA, NA, -0.83, -0.44, -1.26, -1.34, NA, -1.0, -0.98,-1.04, -0.87, NA, -1.04,-0.93, -1.59,-0.68, -0.82, -0.99), type = c(NA, NA, NA, "adjusted", "matched","adjusted", "matched", NA, "adjusted", "matched","adjusted", "matched", NA, "adjusted", "matched","adjusted", "matched", "adjusted", "matched")), .Names = c("Difference", "lower", "upper", "type"), row.names = c(NA, -19L), class = "data.frame")
......以及它的子集:
adjusted <- subset(main_acevccb, type!="matched"|is.na(type)) matched <- subset(main_acevccb, type!="adjusted"|is.na(type))
然后,您将有两个单独的数据框用于调整和匹配的值,并且可以按照链接中的描述继续进行。