Funnel plot: Difference between revisions

Revision as of 19:22, 10 June 2017

Revision as of 17:43, 31 July 2017

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| volume = 315

| issue = 7109

| pages = 629–624629–634

|date=September 1997

| pmid = 9310563

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| volume = 54

| issue = 10

| pages = 1046–10451046–55

|date=October 2001

| pmid = 11576817

| doi = 10.1016/S0895-4356(01)00377-8

}}</ref>

are useful adjuncts to meta-analyses. A funnel plot is a [[scatterplot]] of treatment effect against a measure of study precision. It is used primarily as a visual aid for detecting bias or [[Study heterogeneity|systematic heterogeneity]]. A [[Symmetry|symmetric]] inverted funnel shape arises from a ‘well-behaved’ data set, in which publication bias is unlikely.<ref>{{Cite journal|last=Ijsmi|first=Editor|date=2017-06-10|title=Systematic Review and Meta-Analysis: An overview with the help of R Software|url=http://www.ijsmi.com/Journal/index.php/IJSMI/article/view/7|journal=International Journal of Statistics and Medical Informatics|language=en|volume=3|issue=1|pages=|doi=|via=}}</ref>. An asymmetric funnel indicates a relationship between treatment effect estimate and study precision. This suggests the possibility of either [[publication bias]] or a systematic difference between studies of higher and lower precision (typically ‘small study effects’). Asymmetry can also arise from use of an inappropriate effect measure. Whatever the cause, an asymmetric funnel plot leads to doubts over the appropriateness of a simple meta-analysis and suggests that there needs to be investigation of possible causes.

A variety of choices of measures of ‘study precision’ is available, including total sample size, [[Standard error (statistics)|standard error]] of the treatment effect, and inverse [[variance]] of the treatment effect ([[Weight function|weight]]). Sterne and Egger have compared these with others, and conclude that the standard error is to be recommended.<ref name="SterneJ2001Funnel"/>

When the standard error is used, straight lines may be drawn to define a region within which 95% of points might lie in the absence of both [[Heterogeneous|heterogeneity]] and publication bias.<ref name="SterneJ2001Funnel"/>

In common with [[confidence interval]] plots, funnel plots are conventionally drawn with the treatment effect measure on the [[Cartesian coordinate system|horizontal axis]], so that study precision appears on the vertical axis, breaking with the general rule. Since funnel plots are principally visual aids for detecting asymmetry along the treatment effect axis, this makes them considerably easier to interpret.

== Criticism ==

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| volume = 333

| issue = 7568

| pages = 597–590597–600

|date=September 2006

| doi = 10.1136/bmj.333.7568.597