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Table 3 Contrasts run in Experiment 3

From: Can corrections spread misinformation to new audiences? Testing for the elusive familiarity backfire effect

dV/hypothesis Effect tested F(1,405) P
False-claim inference scores
H1FISl+: NE < FCOl+ Familiarity backfire effect 0.06 .810
H1FISl-: NE < FCOl- Familiarity backfire effect 8.45 .004ab
 H7FIS: FCOl- < FCOl+ Load effect on correction 6.65 .010a
False-claim belief ratings
 H1FBRl-: NE < FCOl- Familiarity backfire effect 6.40 .012ab
 H1FBRl+: NE < FCOl+ Familiarity backfire effect 3.39 .066b
 H7FBR: FCOl- < FCOl+ Load effect on correction 0.45 .501
True-claim inference scores
 H1TISl-: NE < FCOl- Effect of affirmation vs. baseline 19.21 < .001a
 H1TISl+: NE < FCOl+ Effect of affirmation vs. baseline 15.69 < .001a
 H7TIS: FCOl- > FCOl+ Load effect on affirmation 0.18 .671
True-claim belief ratings
 H1TBRl-: NE < FCOl- Effect of affirmation vs. baseline 40.61 < .001a
 H1TBRl+: NE < FCOl+ Effect of affirmation vs. baseline 22.32 < .001a
 H7TBR: FCOl- > FCOl+ Load effect on affirmation 2.60 .108
  1. Note. Hypotheses are numbered H1 and H7 (primary hypotheses in bold; see text for details); subscripts FIS, TIS, FBR, and TBR refer to false-claim and true-claim inference scores and belief ratings, respectively; no-load and load conditions are indicated by l- and l+. Conditions are NE no-exposure; FCOl± fact-check-only with no load or with load. aindicates statistical significance (for secondary contrasts: after Holm-Bonferroni correction). bindicates effect in the opposite of hypothesized direction