Description Usage Arguments Value Examples
From a meta-analysis, analyse for publication bias. Calculates observed and expected number of positive studies and P for difference.
1 2 3 4 | plot_chase_observed_expected(vec_r_events_control,
vec_r_events_treated, vec_n_sample_size_control,
vec_n_sample_size_treated, n, low.alpha, high.alpha,
by.alpha)
|
vec_r_events_control |
an ordered vector of number of events in the untreated group of constituent studies from a meta-analysis. |
vec_r_events_treated |
an ordered vector of number of events in the treated group of constituent studies from a meta-analysis. |
vec_n_sample_size_control |
an ordered vector of the number of participants in the untreated group. |
vec_n_sample_size_treated |
an ordered vector of the number of participants in the treated group. |
n |
Number of iterations used to generate constituent study power; suggest use 10,000. |
low.alpha |
Lower limit of type-1 error rate used to judge whether constituent studies are positive; suggest 0.001. |
high.alpha |
Upper limit of type-1 error rate used to judge whether constituent studies are positive; suggest 0.3. |
by.alpha |
Interval of type-2 error rate at which observed and expected values and P for difference evaluated. |
a dataframe with columns which include alpha level, observed number of positive studies, expected number, and P for difference, OR_hat (summary measure of effect for meta-analysis) with varying levels of significance for constituent studies.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data("BMort") ## Meta-analysis of statin use (Brugts 2009, BMJ)
Btmort<-with(BMort, plot_chase_observed_expected(r_events_control,
r_events_treated, n_sample_size_control, n_sample_size_treated, n=10,
low.alpha=.001, high.alpha=0.3, by.alpha=0.01))
plot(Btmort$alpha, Btmort$observed, type="l", las=1, lwd=2, xlim=c(.0001,0.3),
xlab=c("Significance level"), #### Brugts study mortality outcome; n set low for speed.
ylab=c(""), main=c("(a) Brugts; all-cause mortality."))
lines(Btmort$alpha,Btmort$observed)
lines(Btmort$alpha,Btmort$expected, lty=3)
abline(v=0.05, lty=2)
par(new=TRUE)
plot(Btmort$alpha, Btmort$p.value, type="l", xlab="",lty=4,lwd=2,
col="grey", axes=FALSE, ylab="")
abline(h=0.1, lty=2)
axis(4,las=1)
mtext(side=4,line=2.5,"P for difference")
|
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