Published literature tends to include significant findings, where the data were sufficient to reject the null hypothesis.This can lead to an inflated estimate of effect size when computing a meta-analysis.Rosenthal suggested that researchers test the level of inflation of their effect size calculations by:
A) conducting additional research that would more clearly assess the relationship between variables.
B) pressuring scholarly journals to publish more null findings.
C) computing a file drawer analysis to see how many null findings would be needed to remove the statistical significance found.
D) including studies in their meta-analysis that have strong effects only.

Question

Quizplus · Accepted Answer

Computing a file drawer analysis to see how many null findings would be needed to remove the statistical significance found is the best choice in this situation. This can help researchers determine the extent to which publication bias may be affecting their meta-analysis. Conducting additional research may not be feasible or practical, and pressuring journals to publish more null findings may not address the problem of publication bias. Including studies with strong effects only would also not address the issue of inflated effect size estimates due to publication bias.

Published Literature Tends to Include Significant Findings, Where the Data