Figures: Examples of funnel plots and tests for publication bias

Fig. 1: Funnel plot of black smoke and "daily all cause mortality" in 47 studies.
"This shows an asymmetrical distribution suggestive of publication bias. A formal test of bias was significant p<0.001. Correction for bias using the method of Duval et al (2000) reduced the summary estimate rom 0.6% to 0.5% increase in deaths per 10μg/m³ black smoke." Funnel plot of black smoke and "daily all cause mortality" in 47 studies

Fig. 2: Funnel plot of studies of PM₁₀ and daily mortality used in the WHO (2000).
There is no evidence of bias in the test or the formal plot. Funnel plot of studies of PM10 and daily mortality used in the WHO (2000)

Funnel plot of studies of PM10 and daily mortality used in the WHO (2000)

Fig. 3: Funnel plot of PM2.5 and daily mortality in North American studies.
There is moderate evidence of some bias. Formal test not significant (p<0.08)."

Source: WHO Regional Office for Europe Health Aspects of Air Pollution - answers to follow-up questions from CAFE (2004), Section 5.2

Related publication:

Air Pollution Nitrogen Dioxide

Other Figures & Tables on this publication:

Table 2. Summary of meta-analysis of time-series studies published during the period 1996–2001

Table 3: Summary of studies measuring short-term effect on lung function

Table 4: Short-term effects of ozone on lung function, biological and other responses

Figures: Examples of funnel plots and tests for publication bias

Table 1. Summary estimates for studies of PM10 and daily mortality by GAM or non-GAM statistical model and by single-city or multicity study design.