元分析中缺少 CI 需要进行 Forestplot 调整

Question

这是系统综述，所以我只能分析以前论文提供的数据。对于七个这样的，有足够的数据来构建 CI，我想以通常的森林图方式呈现，包括根据 CI 的长度调整框大小的吸引人的特性。

对于第八个——这里标记为“尴尬”——因为样本量没有透露，我只能显示（最好在同一个森林图上）平均值，而不是 CI。所以，我需要帮助来调整下面的代码，以便在不扭曲其他七个 Okay 框的大小的情况下将这个平均值表示为图上的一个点。

在为 Awkward 添加一个非常窄的 CI 时：要么 CI 太窄并且 R 将值四舍五入导致不显示任何框，要么 CI 太窄以至于森林图库将其解释为“确定”的事物，并且赋予它最高的重量（因此是一个非常大的盒子），这反过来又导致所有其他盒子变得难以区分，并且有点违背目的。一位学生还研究了为 Awkward 分配一个非常大的 CI——这给了 Awkward 一个小框并保持其他状态相对成比例，尽管 Awkward OR 的上限和下限的“胡须”变得很长。

在显示中强制实现所需效果的一种方法可能是为 Awkward 声明一个非常大的 CI（减轻重量），并将该 CI 线打印为白色/透明（因此不可见）；我不知道该怎么做。 （你可能已经猜到了，我绝对是个初学者。）

library(forestplot)

# grafted from https://cran.r-project.org/web/packages/forestplot/vignettes/forestplot.html
##According to this Awkward doesn't have a confidence interval; entries of 0.1 and 30 are fictitious
Table1_19225_OR <- 
  structure(list(
    mean  = c(NA, NA, 6, 4.19, 3.11, 3.79, 13.20, 3.84, 2.32, 5.78, NA, 4.41, 5.99, 5.43), 
    lower = c(NA, NA, 0.1, 2.54, 1.39, 1.83, 6.25, 2.69, 1.04, 2.89, NA, 3.13, 4.65, 4.79),
    upper = c(NA, NA, 30, 6.91, 6.96, 7.85, 27.87, 5.49, 5.2, 11.54, NA, 6.23, 7.71, 6.14)),
    .Names = c("mean", "lower", "upper"), 
    row.names = c(NA, -14L), 
    class = "data.frame")
#State data pooled using random effects model
tabletext<-cbind(
  c("", "State", "Awkward", "Okay1", "Okay2", "Okay3",  "Okay4", "Okay5", "Okay6", "Okay7", NA, "State data", "National", "National"),
  c("Change", "Year", "1977", "1977", "1977", "1982", "1989", "1997", "2000", "2012", NA, "", "1995-2003", "2005-2008"),
  c("Odds", "Ratio", "6.00", "4.19", "3.11", "3.89", "13.20", "3.84", "2.32", "5.78", NA, "4.41", "5.99", "5.43"))

forestplot(tabletext, 
           hrzl_lines = gpar(col="#444444"),
           Table1_19225_OR, new_page = TRUE,
           is.summary=c(TRUE,TRUE,rep(FALSE,9),TRUE,FALSE,FALSE), #TRUE means bold
           clip=c(2, 14), 
           ci.vertices = TRUE,
           xlog=FALSE, 
           xticks = c(2.0, 4.0, 6.0, 8.0, 10, 12),
           grid=TRUE,
           xlab="95% CIs for Odds Ratio",
           col=fpColors(box="royalblue",line="darkblue", summary="royalblue"))

字体大小变化

拥有

Answer 1

由于您无法真正知道场景中的置信区间，我认为最简单的方法是简单地修改置信区间函数以处理缺少数据的绘图值。在下面的示例中，我在下部或上部检查 NA，如果找不到，我绘制 grid.circle 而不是 fpDrawnormalCI 使用的 grid.rect。

library(forestplot)

fn <- function(..., 
               y.offset = 0.5,
               lower_limit, estimate, upper_limit,
               clr.marker){
  if (is.na(lower_limit) || is.na(upper_limit)) {
    grid.circle(x = unit(estimate, "native"), y = y.offset, 
                r = unit(.1, "snpc"), 
                gp = gpar(fill = clr.marker, col = clr.marker))

  } else {
    # Forward otherwise to the default function
    fpDrawNormalCI(..., 
                   y.offset = y.offset,
                   lower_limit = lower_limit, 
                   estimate = estimate,
                   upper_limit = upper_limit,
                   clr.marker = clr.marker)
  }
}

# grafted from https://cran.r-project.org/web/packages/forestplot/vignettes/forestplot.html
##According to this Awkward doesn't have a confidence interval; entries of 0.1 and 30 are fictitious
Table1_19225_OR <- 
  structure(list(
    mean  = c(NA, NA, 6, 4.19, 3.11, 3.79, 13.20, 3.84, 2.32, 5.78, NA, 4.41, 5.99, 5.43), 
    lower = c(NA, NA, NA, 2.54, 1.39, 1.83, 6.25, 2.69, 1.04, 2.89, NA, 3.13, 4.65, 4.79),
    upper = c(NA, NA, NA, 6.91, 6.96, 7.85, 27.87, 5.49, 5.2, 11.54, NA, 6.23, 7.71, 6.14)),
    .Names = c("mean", "lower", "upper"), 
    row.names = c(NA, -14L), 
    class = "data.frame")
#State data pooled using random effects model
tabletext<-cbind(
  c("", "State", "Awkward", "Okay1", "Okay2", "Okay3",  "Okay4", "Okay5", "Okay6", "Okay7", NA, "State data", "National", "National"),
  c("Change", "Year", "1977", "1977", "1977", "1982", "1989", "1997", "2000", "2012", NA, "", "1995-2003", "2005-2008"),
  c("Odds", "Ratio", "6.00", "4.19", "3.11", "3.89", "13.20", "3.84", "2.32", "5.78", NA, "4.41", "5.99", "5.43"))

forestplot(tabletext, 
           Table1_19225_OR, 
           fn.ci_norm = fn,
           hrzl_lines = gpar(col="#444444"),
           new_page = TRUE,
           is.summary=c(TRUE,TRUE,rep(FALSE,9),TRUE,FALSE,FALSE), #TRUE means bold
           clip=c(2, 14), 
           ci.vertices = TRUE,
           xlog=FALSE, 
           xticks = c(2.0, 4.0, 6.0, 8.0, 10, 12),
           grid=TRUE,
           xlab="95% CIs for Odds Ratio",
           col=fpColors(box="royalblue",line="darkblue", summary="royalblue"))

这是情节本身：