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### Function for creating plot when Hedges' g two-independent groups is the effect
# size measure
draw_plot_g <- function(dat, ylim, alpha, pub_bias, prop_sig, pos_sm, pos_me,
pos_la, main, cex.pch)
{
### Create plot
with(dat, plot(x = posi, y = est_cum, type = "p", pch = 16,
ylim = ylim, xlim = c(0, 1), xaxt = "n", yaxt = "n", bty = "n",
xlab = "", las = 1, cex = cex.pch, cex.lab = par()$cex.lab,
ylab = ""))
### Add title to plot
title(main, line = 2.5)
### Add label x-axis
mtext("Precision", side = 1, cex = par()$cex.lab, line = 3.8)
### Add label y-axis
mtext(expression(paste("Effect size (", italic(g), ")"), sep = ""), side = 2,
cex = par()$cex.lab, line = par()$mgp[1])
### Draw confidence intervals
with(dat[nrow(dat), ], arrows(x0 = posi, y0 = lb_cum, y1 = ub_cum, code = 3,
angle = 90, length = 0.1)) # First CI is black
with(dat[1:(nrow(dat)-1), ], arrows(x0 = posi, y0 = lb_cum, y1 = ub_cum, code = 3,
angle = 90, length = 0.1, col = "gray")) # Other CIs gray
### Create x-axis
axis(1, at = seq(0, 1, 0.1), cex = par()$cex.axis)
### Create y-axis
axis(2, at = round(seq(ylim[1], ylim[2], length.out = 8), 2), las = 1)
if (is.na(pub_bias))
{ ### Add points for cumulative meta-analysis based on Mill's ratios if
# proportion statistically significant effect sizes is larger than 0.8 and
# pub_bias is NA
if (prop_sig > 0.8)
{
with(dat, points(x = posi, y = pub_est, cex = cex.pch, pch = 8))
}
} else if (pub_bias == TRUE)
{ ### Add points for cumulative meta-analysis based on Mill's ratios if
# pub_bias is TRUE
with(dat, points(x = posi, y = pub_est, cex = cex.pch, pch = 8))
}
### Vertical line reflecting required sample size for particular statistical power
segments(x0 = pos_la, x1 = pos_la, y0 = par("usr")[3],
y1 = par("usr")[4] + strheight("%"), col = "gray", lty = 2, xpd = TRUE)
segments(x0 = pos_me, x1 = pos_me, y0 = par("usr")[3],
y1 = par("usr")[4] + strheight("%"), col = "gray", lty = 2, xpd = TRUE)
segments(x0 = pos_sm, x1 = pos_sm, y0 = par("usr")[3],
y1 = par("usr")[4] + strheight("%"), col = "gray", lty = 2, xpd = TRUE)
### Horizontal line reflecting estimate of meta-analysis
abline(h = dat$est_cum[nrow(dat)], lty = 3)
### Horizontal line at no effect
abline(h = 0)
### Letters indicating to what effect size each vertical line belongs
text(x = pos_la, y = par("usr")[4] + strheight("%") + (par("usr")[4] + strheight("%"))*0.01,
label = "L", cex = par()$cex.lab*1.2, xpd = TRUE, pos = 3)
text(x = pos_me, y = par("usr")[4] + strheight("%") + (par("usr")[4] + strheight("%"))*0.01,
label = "M", cex = par()$cex.lab*1.2, xpd = TRUE, pos = 3)
text(x = pos_sm, y = par("usr")[4] + strheight("%") + (par("usr")[4] + strheight("%"))*0.01,
label = "S", cex = par()$cex.lab*1.2, xpd = TRUE, pos = 3)
}
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