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The purpose of this paper is to use both conceptual and statistical approaches to explore publication bias in recent causal effects studies in science education, and to draw from this exploration implications for researchers, journal reviewers, and journal editors. This paper fills a void in the "science education" literature as no previous exploration of its kind can be located. The studies in this publication bias analysis are taken from a larger meta-analysis that includes studies from the Unites States, Europe, and East Asia. The general research design is random effects meta-analysis. Specific tests of publication bias were performed within the meta-analysis context. These include funnel plots, Galbraith plots, and Egger's test of Asymmetry. Publication bias was investigated using both intuitive and statistical techniques. The results of this analysis suggest that meta-analyses may not require significant work in the grey literature to produce unbiased results. The data from this 2010-11 study suggest that small effect-small sample studies are being "submitted" for publication and are being "accepted" for publication. One table and four figures are appended.