Table 3.

Overview of Sensitivity Analyses for the Effects of Misinformation, Debunking, and Misinformation-Persistence

Effect Sizes	All	Without Outliers	Any Indication of Bias
A. Contoured-Enhanced Funnel Plot: Funnel plots are scatter plots of the effects estimated from individual records against a measure of study size. Asymmetrical funnel plots suggest publication bias (Sterne & Harbord, 2004). Contour lines, which indicate levels of statistical significance (e.g., < .10, < .05,< .01), are added to funnel plots (Peters et at. 2008). FEM was used.
Misinformation	Asymmetric funnel plot with records fall outside the funnel	Asymmetric funnel plot with records fall outside the funnel	Yes, see Figure 2
Debunking	Asymmetric funnel plot with records fall outside the funnel	-	Yes, see Figure 2
Misinformation-Persistence	Asymmetric funnel plot with records fall outside the funnel	Asymmetric funnel plot with records fall outside the funnel	Yes, see Figure 2
B. Trim and Fill Method: A nonparametric method to correct funnel plot asymmetry by removing the smaller records that cause the asymmetry, re-estimating the center of the effect sizes, and filling the omitted records to ensure that the funnel plot is more symmetrical (Borenstein et al., 2009; Duval, 2005). FEM was used.
Misinformation	Six estimated records filled on the left	Five estimated records filled on the left	Yes, see Figure 2
Debunking	Zero estimated records filled on the left	-	No, see Figure 2
Misinformation-Persistence	Nineteen estimated records filled on the left	Nineteen estimated records filled on the left	Yes, see Figure 2
C. Selection Models: The weight-function models accounting for that effect sizes may not have the same probability of being published. Based on different probabilities, a selection model adjusts estimates of the mean effect size and can be compared with the unadjusted one to assess publication bias (Vevea & Woods, 2005). REM was used.
Misinformation	Small differences between unadjusted and adjusted estimates	Small differences between unadjusted and adjusted estimates	No, see Supplementary Information
Debunking	Large differences between unadjusted and adjusted estimates	-	Yes, see Supplementary Information
Misinformation-Persistence	Small differences between unadjusted and adjusted estimates	Small differences between unadjusted and adjusted estimates	No, see Supplementary Information
D. Meta-Regression Model: Publication type can be examined formally as in a moderator analysis. When data are selectively reported in a way that is related to the magnitude of the effect size (e.g., when results are only reported when they are statistically significant), such a variable can have biasing effects (Borenstein et al., 2009). REM was used.
Misinformation	Publication type was a significant moderator	Publication type was a significant moderator	Yes, see Supplementary Information
Debunking	Publication type was a significant moderator	-	Yes, see Supplementary Information
Misinformation-Persistence	Publication type was a significant moderator	Publication type was a significant moderator	Yes, see Supplementary Information
E. p-Curve: This method involves plotting the distribution of p-values reported in a set of studies. The analysis combines the half (.25) and full p-curve to make inferences about evidential value (Simonsohn, Simmons, & Nelson, 2015).
Misinformation	P-curve was right-skewed	P-curve was right-skewed	No, see Supplementary Information
Debunking	P-curve was right-skewed	-	No, see Supplementary Information
Misinformation-Persistence	P-curve was right-skewed	P-curve was right-skewed	No, see Supplementary Information
F. p-Uniform: This analysis holds the same underlying assumption that the distribution of the p value under the null hypothesis that the effect size is equal to the true effect size is uniform (van Assen et al., 2015). P method was used.
Misinformation	L.pb test was nonsignificant	L.pb test was nonsignificant	No, see Supplementary Information
Debunking	L.pb test was nonsignificant	-	No, see Supplementary Information
Misinformation-Persistence	L.pb test was nonsignificant	L.pb test was nonsignificant	No, see Supplementary Information