The trim-and-fill adjustment increases the contact-prejudice effect estimate, supporting its robustness.
Evidence
Duval and Tweedie’s (2000a, 2000b) “trim-and-fill” method was used to adjust for missing studies by focusing on funnel plot asymmetry. With Z as the effect size and with the random effects model, Duval used her technique to estimate that about 72 (10.3%) samples were missing. When she filled in for these missing data, the effect size estimate increased to a Z of .245, with 95% confidence limits of . to .231. This result suggests a mean effect that is comparable to those reported in Table 1. — Thomas F. Pettigrew, Linda R. Tropp, A Meta-Analytic Test of Intergroup…, 107
Categorization
- XREF: connects to: Trim-and-fill and funnel graph methods tend to overestimate publication bias. — Thomas F. Pettigrew, Linda R. Tropp, A Meta-Analytic Test of Intergroup…, 48
Related
- Trim-and-fill and funnel graph methods tend to overestimate publication bias. (similarity 0.87)
- The contact-prejudice effect may be partly an artifact of publication bias. (similarity 0.82)
- The intergroup contact-prejudice link survives file-drawer checks, indicating limited publication bias. (similarity 0.80)
- A null correlation between sample size and effect size indicates minimal publication bias. (similarity 0.79)
- Meta-analyses overestimate effect sizes because null results go unpublished. (similarity 0.78)
- Publication bias can be detected through sample-size and effect-size correlations. (similarity 0.78)