Computed theoretical power for N=100 and N=200 scenarios
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Modules/ado/plus/m/metabias.hlp
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.-
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help for ^metabias^ (STB-41: sbe19; STB-44: sbe19.1; STB-57: sbe19.2;
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STB-58: sbe19.3; STB-61: sbe19.4)
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.-
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Tests for publication bias in meta-analysis
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-------------------------------------------
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^metabias^ { theta { se_theta | var_theta } | exp(theta) ll ul [cl] }
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[ ^if^ exp ] [ ^in^ range ] [^, by(^by_var^)^ { ^v^ar | ^ci^ }
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^g^raph^(b^egg | ^e^gger^) gw^eight ^l^evel^(^#^)^ graph_options ]
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where { a | b |...} means choose one and only one of {a, b, ...}.
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Description
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-----------
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^metabias^ performs the Begg and Mazumdar adjusted rank correlation test for
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publication bias and performs the Egger, et al., regression asymmetry test for
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publication bias. As options, it provides a funnel graph of the data or the
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regression asymmetry plot.
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The Begg adjusted rank correlation test is a direct statistical analogue of
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the visual funnel graph. Note that both the test and the funnel graph have
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low power for detecting publication bias. The Begg and Mazumdar procedure
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tests for publication bias by determining if there is a significant
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correlation between the effect estimates and their variances. ^metabias^
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carries out this test by, first, standardizing the effect estimates to
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stabilize the variances and, second, performing an adjusted rank correlation
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test based on Kendall's tau.
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The Egger, et al., regression asymmetry test and the regression asymmetry plot
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tend to suggest the presence of publication bias more frequently than the Begg
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approach. The Egger test detects funnel plot asymmetry by determining whether
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the intercept deviates significantly from zero in a regression of the
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standardized effect estimates against their precision.
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Egger, et al., claim that the test predicts the discordance (if any) of
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meta-analytic results and single large trials, but no formal analysis of
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coverage (i.e., nominal significance level) or power has been performed.
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The user provides the effect estimate, ^theta^, to ^metabias^ as a log
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risk ratio, log odds ratio, or other direct measure of effect. Along
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with theta, the user supplies a measure of theta's variability (i.e.,
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its standard error, ^se_theta^, or its variance, ^var_theta^).
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Alternatively, the user may provide the exponentiated form,
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^exp(theta)^, (i.e., a risk ratio or odds ratio) and its confidence
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interval, ^(ll, ul)^.
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The funnel graph plots ^theta^ versus ^se_theta^. Guide lines to assist in
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visualizing the funnel are plotted at the variance-weighted (fixed effects)
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meta-analytic effect estimate and at pseudo confidence interval limits about
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that effect estimate (i.e., at ^theta +/- z * se_theta^, where ^z^ is the
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standard Normal variate for the confidence level specified by option ^level()^.
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Asymmetry on the right of the graph (where studies with high standard error
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are plotted) may give evidence of publication bias.
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The regression asymmetry graph plots the standardized effect estimates,
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^theta / se_theta^, versus precision, ^1 / se_theta^, along with the
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regression line and the confidence interval about the intercept. Failure of
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this confidence interval to include zero indicates asymmetry in the funnel
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plot and may give evidence of publication bias. Guide lines at x = 0 and
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y = 0 are plotted to assist in visually determining if zero is in the
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confidence interval.
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^metabias^ will perform stratified versions of both the Begg and Mazumdar test
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and the Egger regression asymmetry test when option ^by(by_var)^ is specified.
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Variable ^by_var^ indicates the categorical variable that defines the strata.
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The procedure reports results for each strata and for the stratified tests.
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The graphs, if selected, plot only the combined unstratified data.
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Options
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-------
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^by(by_var)^ requests that the stratified tests be carried out with
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strata defined by ^by_var^.
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^var^ indicates that ^var_theta^ was supplied on the command line
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instead of ^se_theta^. Option ^ci^ should not be specified when
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option ^var^ is specified.
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^ci^ indicates that ^exp(theta)^ and its confidence interval, ^(ll,
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ul)^, were supplied on the command line instead of ^theta^ and
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^se_theta^. Option ^var^ should not be specified when option ^ci^ is
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specified.
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^graph(begg)^ requests the Begg funnel graph showing the data, the
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fixed-effects (variance-weighted) meta-analytic effect, and the pseudo
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confidence interval limits about the meta-analytic effect.
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^graph(egger)^ requests the Egger regression asymmetry plot showing the
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standardized effect estimates versus precision, the regression line, and
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the confidence interval about the intercept.
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^gweight^ requests that the graphic symbols representing the data in the
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plot be sized proportional to the inverse variance.
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^level()^ sets the confidence level % for the pseudo confidence intervals;
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the default is 95%.
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^graph_options^ are those allowed with ^graph, twoway^. For
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^graph(begg)^, the default graph_options include ^connect(lll.)^,
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^symbol(iiio)^, and ^pen(3552)^ for displaying the meta-analytic
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effect, the pseudo confidence interval limits (two lines), and the
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data points, respectively. For ^graph(egger)^, the default
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graph_options include ^connect(.ll)^, ^symbol(oid)^, and ^pen(233)^
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for displaying the data points, regression line, and the confidence
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interval about the intercept, respectively. Setting ^t2title(.)^
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blanks out the default ^t2title^ in either graph.
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Required input variables
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------------------------
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^theta^ the effect estimate
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^se_theta^ the corresponding standard error
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or
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^theta^ the effect estimate
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^var_theta^ the corresponding variance
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or
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^exp(theta)^ the risk (or odds) ratio
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^ll^ the lower limit of the risk ratio's confidence interval
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^ul^ the upper limit of the risk ratio's confidence interval
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[^cl^] optional (see below)
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Optional input variable
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-----------------------
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^cl^ contains the confidence level of the confidence interval defined by ^ll^
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and ^ul^. If ^cl^ is not provided, the procedure assumes that each confidence
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interval is at the 95% confidence level. ^cl^ allows the user to provide the
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confidence level, by study, when the confidence interval is not at the default
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level. ^cl^ can be specified with or without a decimal point. For example,
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90 and .90 are equivalent and may be mixed (i.e., 90, .95, 80, .90 etc.).
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Note
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----
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If your data are in raw count format, program ^metan^ can be used to
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facilitate conversion to effect format. ^metan^ automatically adds
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^exp(theta)^ and ^se_theta^ variables to the dataset, calling them
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^_ES^ and ^_seES^. You must manually generate ^theta^ as the natural
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log of ^_ES^ (for example, ^gen _lnES = ln(_ES)^) then input the
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effect-format variables, ^_lnES^ and ^_seES^, using ^metabias^'s
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default input method.
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Saved values
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------------
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The following items are saved in the global ^S_^# macros and are returned in ^r()^.
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^S_1 r(k)^ number of studies
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^S_2 r(score)^ Begg's score
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^S_3 r(score_sd)^ s.d. of Begg's score
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^S_4 r(Begg_p)^ Begg's p value
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^S_5 r(Begg_pcc)^ Begg's p, continuity corrected
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^S_6 r(Egger_bc)^ Egger's bias coefficient
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^S_7 r(Egger_p)^ Egger's p value
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^S_8 r(effect)^ overall effect (log scale)
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Examples
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--------
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. ^metabias logrr selogrr, graph(begg)^
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. ^metabias logrr varlogrr if site==3, var graph(egger)^
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. ^metabias rr ll ul, ci by(site)^
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. ^metabias logor selogor if region==4, graph(egger) level(90)^
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Note
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----
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^metabias^ calls program ^ktau2^, a modification of the ^ktau^ program
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supplied with Stata. ^ktau2^ is included in the distribution files
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for this version of ^metabias^.
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References
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----------
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Begg, C. B., Mazumdar, M., 1994. Operating characteristics of a rank
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correlation test for publication bias. Biometrics 50: 1088-1101.
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Egger, M., Smith, G. D., Schneider, M., Minder, C., 1997. Bias in
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meta-analysis detected by a simple, graphical test. British Medical
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Journal 315: 629-634.
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Author
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------
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Thomas J. Steichen, RJRT, steicht@@rjrt.com
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Also see
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--------
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STB: STB-41 sbe19; STB-44 sbe19.1
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Manual: [R] spearman
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On-line: help for @meta@, @metan@, and @ktau@ (if installed)
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