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help for ^metabias^ (STB-41: sbe19; STB-44: sbe19.1; STB-57: sbe19.2;
STB-58: sbe19.3; STB-61: sbe19.4)
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Tests for publication bias in meta-analysis
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^metabias^ { theta { se_theta | var_theta } | exp(theta) ll ul [cl] }
[ ^if^ exp ] [ ^in^ range ] [^, by(^by_var^)^ { ^v^ar | ^ci^ }
^g^raph^(b^egg | ^e^gger^) gw^eight ^l^evel^(^#^)^ graph_options ]
where { a | b |...} means choose one and only one of {a, b, ...}.
Description
-----------
^metabias^ performs the Begg and Mazumdar adjusted rank correlation test for
publication bias and performs the Egger, et al., regression asymmetry test for
publication bias. As options, it provides a funnel graph of the data or the
regression asymmetry plot.
The Begg adjusted rank correlation test is a direct statistical analogue of
the visual funnel graph. Note that both the test and the funnel graph have
low power for detecting publication bias. The Begg and Mazumdar procedure
tests for publication bias by determining if there is a significant
correlation between the effect estimates and their variances. ^metabias^
carries out this test by, first, standardizing the effect estimates to
stabilize the variances and, second, performing an adjusted rank correlation
test based on Kendall's tau.
The Egger, et al., regression asymmetry test and the regression asymmetry plot
tend to suggest the presence of publication bias more frequently than the Begg
approach. The Egger test detects funnel plot asymmetry by determining whether
the intercept deviates significantly from zero in a regression of the
standardized effect estimates against their precision.
Egger, et al., claim that the test predicts the discordance (if any) of
meta-analytic results and single large trials, but no formal analysis of
coverage (i.e., nominal significance level) or power has been performed.
The user provides the effect estimate, ^theta^, to ^metabias^ as a log
risk ratio, log odds ratio, or other direct measure of effect. Along
with theta, the user supplies a measure of theta's variability (i.e.,
its standard error, ^se_theta^, or its variance, ^var_theta^).
Alternatively, the user may provide the exponentiated form,
^exp(theta)^, (i.e., a risk ratio or odds ratio) and its confidence
interval, ^(ll, ul)^.
The funnel graph plots ^theta^ versus ^se_theta^. Guide lines to assist in
visualizing the funnel are plotted at the variance-weighted (fixed effects)
meta-analytic effect estimate and at pseudo confidence interval limits about
that effect estimate (i.e., at ^theta +/- z * se_theta^, where ^z^ is the
standard Normal variate for the confidence level specified by option ^level()^.
Asymmetry on the right of the graph (where studies with high standard error
are plotted) may give evidence of publication bias.
The regression asymmetry graph plots the standardized effect estimates,
^theta / se_theta^, versus precision, ^1 / se_theta^, along with the
regression line and the confidence interval about the intercept. Failure of
this confidence interval to include zero indicates asymmetry in the funnel
plot and may give evidence of publication bias. Guide lines at x = 0 and
y = 0 are plotted to assist in visually determining if zero is in the
confidence interval.
^metabias^ will perform stratified versions of both the Begg and Mazumdar test
and the Egger regression asymmetry test when option ^by(by_var)^ is specified.
Variable ^by_var^ indicates the categorical variable that defines the strata.
The procedure reports results for each strata and for the stratified tests.
The graphs, if selected, plot only the combined unstratified data.
Options
-------
^by(by_var)^ requests that the stratified tests be carried out with
strata defined by ^by_var^.
^var^ indicates that ^var_theta^ was supplied on the command line
instead of ^se_theta^. Option ^ci^ should not be specified when
option ^var^ is specified.
^ci^ indicates that ^exp(theta)^ and its confidence interval, ^(ll,
ul)^, were supplied on the command line instead of ^theta^ and
^se_theta^. Option ^var^ should not be specified when option ^ci^ is
specified.
^graph(begg)^ requests the Begg funnel graph showing the data, the
fixed-effects (variance-weighted) meta-analytic effect, and the pseudo
confidence interval limits about the meta-analytic effect.
^graph(egger)^ requests the Egger regression asymmetry plot showing the
standardized effect estimates versus precision, the regression line, and
the confidence interval about the intercept.
^gweight^ requests that the graphic symbols representing the data in the
plot be sized proportional to the inverse variance.
^level()^ sets the confidence level % for the pseudo confidence intervals;
the default is 95%.
^graph_options^ are those allowed with ^graph, twoway^. For
^graph(begg)^, the default graph_options include ^connect(lll.)^,
^symbol(iiio)^, and ^pen(3552)^ for displaying the meta-analytic
effect, the pseudo confidence interval limits (two lines), and the
data points, respectively. For ^graph(egger)^, the default
graph_options include ^connect(.ll)^, ^symbol(oid)^, and ^pen(233)^
for displaying the data points, regression line, and the confidence
interval about the intercept, respectively. Setting ^t2title(.)^
blanks out the default ^t2title^ in either graph.
Required input variables
------------------------
^theta^ the effect estimate
^se_theta^ the corresponding standard error
or
^theta^ the effect estimate
^var_theta^ the corresponding variance
or
^exp(theta)^ the risk (or odds) ratio
^ll^ the lower limit of the risk ratio's confidence interval
^ul^ the upper limit of the risk ratio's confidence interval
[^cl^] optional (see below)
Optional input variable
-----------------------
^cl^ contains the confidence level of the confidence interval defined by ^ll^
and ^ul^. If ^cl^ is not provided, the procedure assumes that each confidence
interval is at the 95% confidence level. ^cl^ allows the user to provide the
confidence level, by study, when the confidence interval is not at the default
level. ^cl^ can be specified with or without a decimal point. For example,
90 and .90 are equivalent and may be mixed (i.e., 90, .95, 80, .90 etc.).
Note
----
If your data are in raw count format, program ^metan^ can be used to
facilitate conversion to effect format. ^metan^ automatically adds
^exp(theta)^ and ^se_theta^ variables to the dataset, calling them
^_ES^ and ^_seES^. You must manually generate ^theta^ as the natural
log of ^_ES^ (for example, ^gen _lnES = ln(_ES)^) then input the
effect-format variables, ^_lnES^ and ^_seES^, using ^metabias^'s
default input method.
Saved values
------------
The following items are saved in the global ^S_^# macros and are returned in ^r()^.
^S_1 r(k)^ number of studies
^S_2 r(score)^ Begg's score
^S_3 r(score_sd)^ s.d. of Begg's score
^S_4 r(Begg_p)^ Begg's p value
^S_5 r(Begg_pcc)^ Begg's p, continuity corrected
^S_6 r(Egger_bc)^ Egger's bias coefficient
^S_7 r(Egger_p)^ Egger's p value
^S_8 r(effect)^ overall effect (log scale)
Examples
--------
. ^metabias logrr selogrr, graph(begg)^
. ^metabias logrr varlogrr if site==3, var graph(egger)^
. ^metabias rr ll ul, ci by(site)^
. ^metabias logor selogor if region==4, graph(egger) level(90)^
Note
----
^metabias^ calls program ^ktau2^, a modification of the ^ktau^ program
supplied with Stata. ^ktau2^ is included in the distribution files
for this version of ^metabias^.
References
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Begg, C. B., Mazumdar, M., 1994. Operating characteristics of a rank
correlation test for publication bias. Biometrics 50: 1088-1101.
Egger, M., Smith, G. D., Schneider, M., Minder, C., 1997. Bias in
meta-analysis detected by a simple, graphical test. British Medical
Journal 315: 629-634.
Author
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Thomas J. Steichen, RJRT, steicht@@rjrt.com
Also see
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STB: STB-41 sbe19; STB-44 sbe19.1
Manual: [R] spearman
On-line: help for @meta@, @metan@, and @ktau@ (if installed)