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Christian Roever
bayesmeta
Commits
48cba497
Commit
48cba497
authored
3 years ago
by
Christian Roever
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re-introduced 'traceplot.bmr()' function
parent
e330584a
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NAMESPACE
+1
-0
1 addition, 0 deletions
NAMESPACE
R/bmr.R
+126
-0
126 additions, 0 deletions
R/bmr.R
man/traceplot.bayesmeta.Rd
+5
-2
5 additions, 2 deletions
man/traceplot.bayesmeta.Rd
with
132 additions
and
2 deletions
NAMESPACE
+
1
−
0
View file @
48cba497
...
...
@@ -39,6 +39,7 @@ S3method(summary, bmr)
S3method(plot, bmr)
S3method(pairs, bmr)
S3method(forestplot, bmr)
S3method(traceplot, bmr)
importFrom("grDevices",
"grey", "rainbow", "rgb")
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R/bmr.R
+
126
−
0
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48cba497
...
...
@@ -2097,3 +2097,129 @@ forestplot.bmr <- function(x,
"labeltext"
=
labeltext
,
"forestplot"
=
fp
))
}
traceplot.bmr
<-
function
(
x
,
mulim
,
taulim
,
ci
=
FALSE
,
rightmargin
=
8
,
col
=
rainbow
(
x
$
k
),
...
)
{
stopifnot
(
missing
(
mulim
)
||
(
length
(
mulim
)
==
2
),
missing
(
taulim
)
||
(
length
(
taulim
)
<=
2
),
rightmargin
>=
0
,
length
(
col
)
==
x
$
k
)
q975
<-
qnorm
(
0.975
)
gridcol
<-
"grey85"
# convert "taulim" and "mulim" arguments
# to eventual "taurange" and "murange" vectors:
if
(
!
missing
(
taulim
)
&&
all
(
is.finite
(
taulim
)))
{
if
((
length
(
taulim
)
==
2
)
&&
(
taulim
[
1
]
>=
0
)
&&
(
taulim
[
2
]
>
taulim
[
1
]))
taurange
<-
taulim
else
if
((
length
(
taulim
)
==
1
)
&&
(
taulim
>
0
))
taurange
<-
c
(
0
,
taulim
)
else
taurange
<-
c
(
0
,
x
$
qposterior
(
tau
=
0.995
)
*
1.1
)
}
else
{
taurange
<-
c
(
0
,
x
$
qposterior
(
tau
=
0.995
)
*
1.1
)
}
vertlines
<-
pretty
(
taurange
)
if
(
!
missing
(
mulim
)
&&
(
all
(
is.finite
(
mulim
))
&&
(
mulim
[
1
]
<
mulim
[
2
])))
{
murange
<-
mulim
}
else
{
cm
<-
matrix
(
NA_real_
,
nrow
=
x
$
k
,
ncol
=
2
,
dimnames
=
list
(
"study"
=
x
$
labels
,
"moments"
=
c
(
"mean"
,
"sd"
)))
for
(
i
in
1
:
x
$
k
)
cm
[
i
,]
<-
x
$
shrink.moments
(
tau
=
taurange
[
2
],
which
=
i
)
if
(
ci
){
murange
<-
range
(
c
(
cm
[,
"mean"
]
-
q975
*
cm
[,
"sd"
],
cm
[,
"mean"
]
+
q975
*
cm
[,
"sd"
]))
}
else
{
murange
<-
range
(
cm
[,
"mean"
])
}
murange
<-
murange
+
c
(
-1
,
1
)
*
diff
(
murange
)
*
0.05
}
mutrace
<-
function
(
x
)
{
# range of tau values:
tau
<-
seq
(
max
(
c
(
0
,
taurange
[
1
]
-0.1
*
diff
(
taurange
))),
taurange
[
2
]
+0.1
*
diff
(
taurange
),
le
=
200
)
cm.indiv
<-
array
(
NA_real_
,
dim
=
c
(
length
(
tau
),
2
,
x
$
k
),
dimnames
=
list
(
NULL
,
c
(
"mean"
,
"sd"
),
x
$
labels
))
for
(
i
in
1
:
x
$
k
)
{
cm.indiv
[,,
i
]
<-
x
$
shrink.moment
(
tau
=
tau
,
which
=
i
)
}
plot
(
taurange
,
murange
,
type
=
"n"
,
axes
=
FALSE
,
xlab
=
""
,
ylab
=
"effect"
,
main
=
""
,
...
)
abline
(
v
=
vertlines
,
col
=
gridcol
)
abline
(
h
=
pretty
(
murange
),
col
=
gridcol
)
abline
(
v
=
0
,
col
=
grey
(
0.40
))
# grey shading:
if
(
ci
)
{
for
(
i
in
1
:
x
$
k
)
{
polygon
(
c
(
tau
,
rev
(
tau
)),
c
(
cm.indiv
[,
"mean"
,
i
]
-
q975
*
cm.indiv
[,
"sd"
,
i
],
rev
(
cm.indiv
[,
"mean"
,
i
]
+
q975
*
cm.indiv
[,
"sd"
,
i
])),
col
=
grey
(
0.75
,
alpha
=
0.25
),
border
=
NA
)
}
}
# individual estimates:
matlines
(
tau
,
cm.indiv
[,
"mean"
,],
col
=
col
,
lty
=
1
)
if
(
ci
)
{
matlines
(
tau
,
cm.indiv
[,
"mean"
,]
-
q975
*
cm.indiv
[,
"sd"
,],
col
=
col
,
lty
=
3
)
matlines
(
tau
,
cm.indiv
[,
"mean"
,]
+
q975
*
cm.indiv
[,
"sd"
,],
col
=
col
,
lty
=
3
)
}
axis
(
2
)
for
(
i
in
1
:
x
$
k
)
axis
(
side
=
4
,
at
=
cm.indiv
[
length
(
tau
),
"mean"
,
i
],
labels
=
x
$
labels
[
i
],
tick
=
FALSE
,
col.axis
=
col
[
i
],
las
=
1
)
invisible
()
}
taumarginal
<-
function
(
x
)
# NB: function is (essentially) identical to the one within "plot.bayesmeta()"
{
# range of tau values:
tau
<-
seq
(
max
(
c
(
0
,
taurange
[
1
]
-0.1
*
diff
(
taurange
))),
taurange
[
2
]
+0.1
*
diff
(
taurange
),
le
=
200
)
# corresponding posterior density:
dens
<-
x
$
dposterior
(
tau
=
tau
)
# empty plot:
maxdens
<-
max
(
dens
[
is.finite
(
dens
)],
na.rm
=
TRUE
)
plot
(
c
(
taurange
[
1
],
taurange
[
2
]),
c
(
0
,
maxdens
),
type
=
"n"
,
axes
=
FALSE
,
xlab
=
""
,
ylab
=
""
,
main
=
""
)
abline
(
v
=
vertlines
,
col
=
gridcol
)
# "fix" diverging density:
dens
[
!
is.finite
(
dens
)]
<-
10
*
maxdens
# light grey shaded contour for density across whole range:
polygon
(
c
(
0
,
tau
,
max
(
tau
)),
c
(
0
,
dens
,
0
),
border
=
NA
,
col
=
grey
(
0.90
))
# dark grey shaded contour for density within 95% bounds:
indi
<-
((
tau
>=
x
$
summary
[
"95% lower"
,
"tau"
])
&
(
tau
<=
x
$
summary
[
"95% upper"
,
"tau"
]))
polygon
(
c
(
rep
(
x
$
summary
[
"95% lower"
,
"tau"
],
2
),
tau
[
indi
],
rep
(
x
$
summary
[
"95% upper"
,
"tau"
],
2
)),
c
(
0
,
min
(
c
(
x
$
dposterior
(
tau
=
x
$
summary
[
"95% lower"
,
"tau"
]),
10
*
maxdens
)),
dens
[
indi
],
x
$
dposterior
(
tau
=
x
$
summary
[
"95% upper"
,
"tau"
]),
0
),
border
=
NA
,
col
=
grey
(
0.80
))
# vertical line at posterior median:
lines
(
rep
(
x
$
summary
[
"median"
,
"tau"
],
2
),
c
(
0
,
x
$
dposterior
(
tau
=
x
$
summary
[
"median"
,
"tau"
])),
col
=
grey
(
0.6
))
# actual density line:
lines
(
tau
,
dens
,
col
=
"black"
)
# x-axis, y-axis:
abline
(
h
=
0
,
v
=
0
,
col
=
grey
(
0.40
))
# add axes, labels, bounding box, ...
mtext
(
side
=
1
,
line
=
par
(
"mgp"
)[
1
],
expression
(
"heterogeneity "
*
tau
))
#mtext(side=2, line=par("mgp")[2], expression("marginal posterior density"))
axis
(
1
)
#; box()
invisible
()
}
# make sure to re-set graphical parameters later:
prevpar
<-
par
(
no.readonly
=
TRUE
)
on.exit
(
par
(
prevpar
))
# generate actual plot:
graphics
::
layout
(
rbind
(
1
,
2
),
heights
=
c
(
2
,
1
))
par
(
mar
=
c
(
-0.1
,
3
,
0
,
rightmargin
)
+0.1
,
mgp
=
c
(
2.0
,
0.8
,
0
))
mutrace
(
x
)
par
(
mar
=
c
(
3
,
3
,
-0.1
,
rightmargin
)
+0.1
)
taumarginal
(
x
)
graphics
::
layout
(
1
)
par
(
mar
=
c
(
5
,
4
,
4
,
2
)
+0.1
)
invisible
()
}
This diff is collapsed.
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man/traceplot.bayesmeta.Rd
+
5
−
2
View file @
48cba497
...
...
@@ -2,6 +2,7 @@
\alias{traceplot}
\alias{traceplot.default}
\alias{traceplot.bayesmeta}
\alias{traceplot.bmr}
\title{
Illustrate conditional means of overall effect as well as study-specific
estimates as a function of heterogeneity.
...
...
@@ -15,10 +16,12 @@
traceplot(x, ...)
\method{traceplot}{bayesmeta}(x, mulim, taulim, ci=FALSE,
rightmargin=8, col=rainbow(x$k), ...)
\method{traceplot}{bmr}(x, mulim, taulim, ci=FALSE,
rightmargin=8, col=rainbow(x$k), ...)
}
\arguments{
\item{x}{
a \code{\link{bayesmeta}} object.
a \code{\link{bayesmeta}}
or \code{\link{bmr}}
object.
}
\item{mulim, taulim}{(optional) ranges for the effect (mu) and
heterogeneity (tau) axes. If only one value is given for
...
...
@@ -75,7 +78,7 @@
\doi{10.3102/10769986006004377}.
}
\seealso{
\code{\link{bayesmeta}}.
\code{\link{bayesmeta}}
, \code{\link{bmr}}
.
}
\examples{
# load example data:
...
...
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