H.R. Rothstein, A.J. Sutton, & M. Borenstein (Eds.) (2005). Publication bias in meta-analysis: Prevention, assessment and adjustments. NewYork: Wiley, xvii+356 p. US$100.00. ISBN: 0-470-87014-1.

Abstract

Each study that is published about the effect of an independent variable on a dependent one, or the strength of the relationship between two variables, constitutes only a single piece in a constantly growing body of evidence.For example, over one hundred studies have been carried out to determine the relationship between employment interview performance and job performance (McDaniel, Whetzel, Schmidt, & Maurer, 1994).Each study yields a measure of the strength and direction of the association, typically in the form of a correlation coefficient.In some studies, the correlation coefficient is statistically significant, while others do not find a statistically significant association.To make sense of the often-conflicting results found in the literature, one can conduct a meta-analysis (e.g., Cooper, 1998; Cooper & Hedges, 1994;Hedges & Olkin, 1985;Hunter & Schmidt, 2004;Lipsey & Wilson, 2001;Rosenthal, 1991).In essence, the correlation coefficients that we extract from the various studies then become the data for further analysis.For example, if we assume that the observed correlation coefficients only differ from each other due to sampling variability, then the average of the correlation coefficients provides an estimate of the overall validity of employment interviews.However, if the correlation coefficients of published studies differ systematically from those of unpublished studies, then the estimate may be biased (e.g., when studies with statistically significant results are more likely to be published, then the true correlation may be overestimated).In fact, regardless of whether we use meta-analysis, or simply conduct a narrative review to synthesize the relevant literature, the conclusions that we draw may be wrong if the accessible studies (and these typically coincide to a great deal with the ones we find in the published literature) differ systematically from the population of completed studies.This is known as the publication bias problem and constitutes the topic of the book Publication bias in meta-analysis: Prevention, assessment and adjustments, edited by Rothstein, Sutton, and Borenstein (2005).This is the first book to address this issue in such detail and is likely to become a standard reference for those who carry out systematic literature reviews.The chapters, which were written by leading experts in the field of research synthesis, summarize a substantial amount of research that has been conducted on the issue of publication bias.The following topics are addressed in the chapters:• various forms of publication bias, evidence of its existence, the extent of its influence, and potential causes and consequences of publication bias; • statistical techniques for detecting publication bias, for assessing the sensitivity of conclusions to the possible presence of publication bias, and for adjusting meta-analytic estimates for publication bias; • capabilities of various software packages with respect to these techniques; • strategies for eliminating or at least minimizing the influence of publication bias;• other forms of missing data or data suppression mechanisms besides publication bias that may bias the conclusions from systematic literature reviews; and • other factors that may mimic the appearance of publication bias, but should not be confused with it.