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### library(metafor); library(testthat); Sys.setenv(NOT_CRAN="true")
### see also: https://www.metafor-project.org/doku.php/plots:gosh_plot
source("settings.r")
context("Checking plots example: GOSH plot")
test_that("plot can be drawn.", {
expect_equivalent(TRUE, TRUE) # avoid 'Empty test' message
skip_on_cran()
### meta-analysis of all trials including ISIS-4 using an equal-effects model
res <- rma(measure="OR", ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat.egger2001, method="EE")
### fit EE model to all possible subsets
sav <- gosh(res, progbar=FALSE)
out <- capture.output(print(sav)) # so that print.gosh.rma() is run (at least once)
### create GOSH plot
### red points for subsets that include and blue points
### for subsets that exclude study 16 (the ISIS-4 trial)
png("images/test_plots_gosh_1_test.png", res=200, width=1800, height=1800, type="cairo")
plot(sav, out=16, breaks=100)
dev.off()
expect_true(.vistest("images/test_plots_gosh_1_test.png", "images/test_plots_gosh_1.png"))
### fit EE model to random subsets (with parallel processing)
sav <- gosh(res, progbar=FALSE, parallel="snow", subsets=1000)
### meta-analysis using MH method (using subset to speed things up)
res <- rma.mh(measure="OR", ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat.egger2001, subset=c(1:7,16))
sav <- gosh(res, progbar=FALSE)
### create GOSH plot
png("images/test_plots_gosh_2_test.png", res=200, width=1800, height=1800, type="cairo")
plot(sav, out=8, breaks=40)
dev.off()
expect_true(.vistest("images/test_plots_gosh_2_test.png", "images/test_plots_gosh_2.png"))
### fit EE model to all possible subsets (with parallel processing)
sav <- gosh(res, progbar=FALSE, parallel="snow", subsets=1000)
### meta-analysis using Peto's method (using subset to speed things up)
res <- rma.peto(ai=ai, n1i=n1i, ci=ci, n2i=n2i, data=dat.egger2001, subset=c(1:7,16))
sav <- gosh(res, progbar=FALSE)
### create GOSH plot
png("images/test_plots_gosh_3_test.png", res=200, width=1800, height=1800, type="cairo")
plot(sav, out=8, breaks=40)
dev.off()
expect_true(.vistest("images/test_plots_gosh_3_test.png", "images/test_plots_gosh_3.png"))
### fit EE model to all possible subsets (with parallel processing)
sav <- gosh(res, progbar=FALSE, parallel="snow", subsets=1000)
})
rm(list=ls())
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