metabias {meta} | R Documentation |
Test for funnel plot asymmetry, based on rank correlation or linear regression method.
metabias(x, seTE, TE.fixed, seTE.fixed, method = "rank", plotit = FALSE, correct = FALSE)
x |
An object of class meta , or estimated treatment
effect in individual studies. |
seTE |
Standard error of estimated treatment effect (mandatory if
x not of class meta ). |
TE.fixed |
Overall treatment estimate (mandatory if x not
of class meta and method = "rank" ). |
seTE.fixed |
Standard error of overall treatment estimate
(mandatory if x not of class meta and method =
"rank" ). |
method |
A character string indicating which test is to be
used. Either "rank" , "linreg" , "mm" or
"count" , can be abbreviated. |
plotit |
A logical indicating whether a plot should be produced
for method "rank" , "linreg" or "mm" . |
correct |
A logical indicating whether a continuity corrected
statistic is used for rank correlation methods "rank" and "count" . |
If method
is "rank"
, the test statistic is based on the
rank correlation between standardised treatment estimates and variance
estimates of estimated treatment effects; Kendall's tau is used as
correlation measure (Begg & Mazumdar, 1994). The test statistic
follows a standard normal distribution. By default (if correct
is FALSE), no continuity correction is utilised (Kendall & Gibbons,
1990).
If method
is "linreg"
, the test statistic is based on a
linear regression of the standardised treatment effect (standard
normal deviate) on the inverse of the standard error of the treatment
estimate (Egger et al., 1997). The test statistic follows a t
distribution with number of studies - 2
degrees of freedom.
If method
is "mm"
, the test statistic is based on a
weighted linear regression using the method of moments estimator of
the additive between-study variance component (method 3a in Thompson,
Sharp, 1999). The test statistic follows a t distribution with
number of studies - 2
degrees of freedom.
If method
is "count"
, the test statistic is based on the
rank correlation between a standardised cell frequency and the inverse
of the variance of the cell frequency; Kendall's tau is used as
correlation measure (Schwarzer, 2003). The test statistic
follows a standard normal distribution. By default (if correct
is FALSE), no continuity correction is utilised (Kendall & Gibbons,
1990).
A list with class "htest"
containing the following components:
estimate |
the estimated degree of funnel plot asymmetry, with
name "ks" or "bias" corresponding to the method
employed, i.e., rank correlation or regression method. |
statistic |
The value of the test statistic. |
parameter |
The degrees of freedom of the test statistic in the case that it follows a t distribution. |
p.value |
The p-value for the test. |
null.value |
The value of test statistic under the
null hypothesis, always 0 . |
alternative |
A character string describing the alternative hypothesis. |
method |
A character string indicating what type of test was used. |
data.name |
A character string giving the names of the data. |
Guido Schwarzer sc@imbi.uni-freiburg.de
Begg CB & Berlin JA (1994), Operating characteristics of a rank correlation test for publication bias. Biometrics, 50, 1088–1101.
Kendall M & Gibbons JD (1990), Rank Correlation Methods. London: Edward Arnold.
Egger M, Smith GD, Schneider M & Minder C (1997), Bias in meta-analysis detected by a simple, graphical test. British Medical Journal, 315, 629–634.
Schwarzer G (2003), Statistical Tests for Bias in Meta-Analysis with Binary Outcomes, PhD thesis, University of Dortmund, Germany, http://eldorado.uni-dortmund.de
Thompson SG, Sharp, SJ (1999), Explaining heterogeneity in meta-analysis: A comparison of methods, Statistics in Medicine, 18, 2693–2708.
funnel
, metabin
, metacont
, metagen
data(Olkin95) meta1 <- metabin(event.e, n.e, event.c, n.c, data=Olkin95, subset=c(41,47,51,59), sm="RR", meth="I") metabias(meta1) metabias(meta1, correct=TRUE) metabias(meta1, method="linreg") metabias(meta1, method="linreg", plotit=TRUE) metabias(meta1, method="count") ## ## Same result: ## metabias(meta1, method="linreg")$p.value metabias(meta1$TE, meta1$seTE, method="linreg")$p.value