smd2or | R Documentation |
Conversion from standardised mean difference to log odds ratio using method by Hasselblad & Hedges (1995) or Cox (1970).
smd2or(
smd,
se.smd,
studlab,
data = NULL,
subset = NULL,
exclude = NULL,
method = "HH",
backtransf = gs("backtransf"),
...
)
smd |
Standardised mean difference(s) (SMD) or meta-analysis object. |
se.smd |
Standard error(s) of SMD (ignored if argument
|
studlab |
An optional vector with study labels (ignored if
argument |
data |
An optional data frame containing the study information
(ignored if argument |
subset |
An optional vector specifying a subset of studies to
be used (ignored if argument |
exclude |
An optional vector specifying studies to exclude
from meta-analysis, however, to include in printouts and forest
plots (ignored if argument |
method |
A character string indicating which method is used to
convert SMDs to log odds ratios. Either |
backtransf |
A logical indicating whether odds ratios (if TRUE) or log odds ratios (if FALSE) should be shown in printouts and plots. |
... |
Additional arguments passed on to
|
This function implements the following methods for the conversion from standardised mean difference to log odds ratio:
Hasselblad & Hedges (1995) assuming logistic distributions
(method == "HH"
)
Cox (1970) and Cox & Snell (1989) assuming normal
distributions (method == "CS"
)
Internally, metagen
is used to conduct a
meta-analysis with the odds ratio as summary measure.
Argument smd
can be either a vector of standardised mean
differences or a meta-analysis object created with
metacont
or metagen
and the
standardised mean difference as summary measure.
Argument se.smd
is mandatory if argument smd
is a
vector and ignored otherwise. Additional arguments in ...
are only passed on to metagen
if argument smd
is a vector.
An object of class c("metagen", "meta")
with corresponding
generic functions (see meta-object
).
Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de
Borenstein M, Hedges LV, Higgins JPT, Rothstein HR (2009): Introduction to Meta-Analysis. Chichester: Wiley
Cox DR (1970): Analysis of Binary Data. London: Chapman and Hall / CRC
Cox DR, Snell EJ (1989): Analysis of Binary Data (2nd edition). London: Chapman and Hall / CRC
Hasselblad V, Hedges LV (1995): Meta-analysis of screening and diagnostic tests. Psychological Bulletin, 117, 167–78
or2smd
, metacont
,
metagen
, metabin
# Example from Borenstein et al. (2009), Chapter 7
#
mb <- smd2or(0.5, sqrt(0.0205), backtransf = FALSE)
# TE = log odds ratio; seTE = standard error of log odds ratio
data.frame(lnOR = round(mb$TE, 4), varlnOR = round(mb$seTE^2, 4))
# Use dataset from Fleiss (1993)
#
data(Fleiss1993cont)
m1 <- metacont(n.psyc, mean.psyc, sd.psyc, n.cont, mean.cont, sd.cont,
data = Fleiss1993cont, sm = "SMD",
studlab = paste(study, year))
smd2or(m1)
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