Publication bias is the tendency to decide to publish a study based on the results of the study, rather than on the basis of its theoretical or methodological quality. It can arise from selective publication of favorable results, or of statistically significant results. This threatens the validity of conclusions drawn from reviews of published scientific research. Meta-analysis is now used in numerous scientific disciplines, summarizing quantitative evidence from multiple studies. If the literature being synthesised has been affected by publication bias, this in turn biases the meta-analytic results, potentially producing overstated conclusions. Publication Bias in Meta-Analysis examines the different types of publication bias, and presents the methods for estimating and reducing publication bias, or eliminating it altogether. It is written by leading experts, adopting a practical and multidisciplinary approach. It provides comprehensive coverage of the topic, including: different types of publication bias and mechanisms that may induce them; empirical evidence for their existence; statistical methods to address them; and, ways in which they can be avoided. It also features worked examples and common data sets throughout. It explains and compares all available software used for analysing and reducing publication bias. Accompanied by a website featuring software, data sets and further material, Publication Bias in Meta-Analysis adopts an inter-disciplinary approach and will make an excellent reference volume for any researchers and graduate students who conduct systematic reviews or meta-analyses. University and medical libraries, as well as pharmaceutical companies and government regulatory agencies, will also find this invaluable.