cidprop.meta {meta} | R Documentation |
Calculate expected proportion of comparable studies with clinically important benefit or harm
Description
Calculate expected proportion of comparable studies with clinically important benefit or harm which is derived from the prediction interval.
Usage
## S3 method for class 'meta'
cidprop(
x,
cid = NULL,
cid.below.null = NULL,
cid.above.null = NULL,
label.cid = "",
label.cid.below.null = NULL,
label.cid.above.null = NULL,
small.values = "desirable",
...
)
cidprop(x, ...)
## S3 method for class 'cidprop'
print(
x,
digits.cid = gs("digits.cid"),
digits.percent = 1,
big.mark = gs("big.mark"),
details.methods = gs("details"),
...
)
Arguments
x |
An object of class |
cid |
A numeric value or vector specifying clinically important differences (CID) / decision thresholds used to calculate expected proportions of clinically important benefit or harm (see Details). |
cid.below.null |
A numeric value or vector specifying CID limits below the null effect (see Details). |
cid.above.null |
A numeric value or vector specifying CID limits above the null effect (see Details). |
label.cid |
A character string or vector specifying labels for
clinically important differences. Must be of same length as argument
|
label.cid.below.null |
A character string or vector specifying labels
for clinically important differences below the null effect. Must be of
same length as argument |
label.cid.above.null |
A character string or vector specifying labels
for clinically important differences above the null effect. Must be of
same length as argument |
small.values |
A character string specifying whether small
treatment effects indicate a beneficial ( |
... |
Additional arguments (ignored) |
digits.cid |
Minimal number of significant digits for
CIDs / decision thresholds, see |
digits.percent |
Minimal number of significant digits for
expected proportions, printed as percentages, see |
big.mark |
A character used as thousands separator. |
details.methods |
A logical specifying whether details on statistical methods should be printed. |
Details
Expected proportions of comparable studies with clinically important benefit or harm are derived from the prediction interval in the meta-analysis.
Clinically important benefit or harm can be defined using either argument
cid
or cid.below.null
and cid.above.null
.
Input for the later arguments will be ignored if argument cid
was
specified. In this case, the values of cid.below.null
and
cid.above.null
will be equal to
-
cid
and1 / cid
for ratio measures, -
cid
and-cid
for difference measures.
Thresholds based on argument cid
will always be symmetric. Asymmetric
thresholds can be defined using arguments cid.below.null
and
cid.above.null
.
Value
A list with elements
prop.cid.below.null |
Expected proportion of comparable studies below lower CID(s) |
prop.cid.above.null |
Expected proportion of comparable studies above upper CID(s) |
prop.within.cid |
Expected proportion of comparable studies between lower and upper CID(s) |
cid , cid.below.null , cid.above.null , small.values , x |
As defined above |
label.cid , label.cid.below.null , label.cid.above.null |
As defined above |
Author(s)
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
See Also
Examples
oldset <- settings.meta(digits.cid = 0)
m <- metagen(1:10 - 3, 1:10, sm = "MD")
#
pp1 <- cidprop(m, cid = 2)
pp1
#
pp2 <- cidprop(m, cid.below = 0.5, cid.above = 2)
pp2
#
pp3 <- cidprop(m, cid.below = 0.5, cid.above = 2, small.values = "u")
pp3
pp4 <- cidprop(m, cid = 1:2, label.cid = c("moderate", "large"))
pp4
#
pp5 <- cidprop(m, cid.below = -1.5, cid.above = 1:2,
label.cid.below = "large", label.cid.above = c("moderate", "large"))
pp5
settings.meta(oldset)