格子中跨面板的条件层

Condition layer across panels in lattice

我想在带有两个面板的格子 stripplot 中针对两种不同条件绘制单个主题均值。我还想添加我计算并存储在单独数据框中的主题内置信区间。我试图用 latticeExtra 的 layer 函数覆盖这些置信区间。当我添加图层时,如果我将 [subscripts] 添加到 x's 和 y's,则两组间隔显示在两个面板上(如下面的代码和第一张图片所示)或两组间隔仅显示在第一个面板上layer 命令(如下面的第二个代码片段和图片所示)。如何获得适当的时间间隔以显示在适当的面板上?

library(latticeExtra)

raw_data <- data.frame(subject = rep(1:6, 4), cond1 = as.factor(rep(1:2, each = 12)), cond2 = rep(rep(c("A", "B"), each = 6), 2), response = c(2:7, 6:11, 3:8, 7:12))
summary_data <- data.frame(cond1 = as.factor(rep(1:2, each = 2)), cond2 = rep(c("A", "B"), times = 2), mean = aggregate(response ~ cond2 * cond1, raw_data, mean)$response, within_ci = c(0.57, 0.54, 0.6, 0.63))
summary_data$lci <- summary_data$mean - summary_data$within_ci
summary_data$uci <- summary_data$mean + summary_data$within_ci

subject_stripplot <- stripplot(response ~ cond1 | cond2, groups = subject, data = raw_data, 
  panel = function(x, y, ...) {
    panel.stripplot(x, y, type = "b", lty = 2, ...)
    panel.average(x, y, fun = mean, lwd = 2, col = "black", ...)    # plot line connecting means
  }
)
addWithinCI <- layer(panel.segments(x0 = cond1, y0 = lci, x1 = cond1, y1 = uci, subscripts = TRUE), data = summary_data, under = FALSE)
plot(subject_stripplot + addWithinCI)

两个面板上都有两组间隔的带状图:

addWithinCI2 <- layer(panel.segments(x0 = cond1[subscripts], y0 = lci[subscripts], x1 = cond1[subscripts], y1 = uci[subscripts], subscripts = TRUE), data = summary_data, under = FALSE)
plot(subject_stripplot + addWithinCI2)

只有第一个面板上有两组间隔的带状图

一个可能的解决方案是 print 条带图(例如,在 png 或任何其他图形设备中),然后使用 trellis.focus 修改每个子面板。

## display stripplot
print(subject_stripplot)

## loop over grops
for (i in c("A", "B")) {

  # subset of current group
  dat <- subset(summary_data, cond2 == i)

  # add intervals to current panel
  trellis.focus(name = "panel", column = ifelse(i == "A", 1, 2), row = 1)
  panel.segments(x0 = dat$cond1, y0 = dat$lci, 
                 x1 = dat$cond1, y1 = dat$uci, subscripts = TRUE)
  trellis.unfocus()
}

另一个(可能更方便)的解决方案是创建一个单独的 xyplot 并设置传递给 [=18 的下限和上限 y 值(y0y1) =] 手动依赖于当前 panel.number。与使用 trellis.focus 的初始方法相比,这样创建的图可以存储在变量中,因此可用于 R 中的后续处理。

p_seg <- xyplot(lci ~ cond1 | cond2, data = summary_data, ylim = c(1, 13),
       panel = function(...) {
         # lower and upper y values
         y0 <- list(summary_data$lci[c(1, 3)], summary_data$lci[c(2, 4)])
         y1 <- list(summary_data$uci[c(1, 3)], summary_data$uci[c(2, 4)])
         # insert vertical lines depending on current panel
         panel.segments(x0 = 1:2, x1 = 1:2,
                        y0 = y0[[panel.number()]], 
                        y1 = y1[[panel.number()]])
       })

p_comb <- subject_stripplot + 
  as.layer(p_seg)

# print(p_comb)

另一种不需要 latticeExtra 的解决方案(来自 Duncan Mackay):

summary_data$cond3 <- sapply(summary_data$cond2, pmatch, LETTERS)

mypanel <- function(x, y, ..., lci, uci, scond1, scond3, groups, type, lty){
pnl = panel.number()
panel.xyplot(x, y, ..., groups = groups, type = type, lty = lty)
panel.average(x, y, horizontal = FALSE, col = "black", lwd = 3)
panel.segments(x0 = scond1[scond3 == pnl],
               y0 = lci[scond3 == pnl],
               x1 = scond1[scond3 == pnl],
               y1 = uci[scond3 == pnl])
}
with(summary_data,
 stripplot(response ~ cond1 | cond2, data = raw_data,
           groups = subject,
           lci = lci,
           uci = uci,
           scond1 = summary_data$cond1,
           scond3 = cond3,
           type = "b",
           lty = 2,
           panel = mypanel)
)