This chapter covers the concepts of error and bias and their application in practice using a total error framework. This includes a discussion of how to manage both sampling and non-sampling error, and covers ways to assess and address coverage bias, nonresponse bias, measurement error, and estimation error.

Meta-analysis is a well-established approach to integrating research findings, with a long history in the sciences and in psychology in particular. Its use in summarizing research findings has special significance given increasing concerns about scientific replicability, but it has other important uses as well, such as integrating information across studies to examine models that might otherwise be too difficult to study in a single sample. This chapter discusses different forms and purposes of meta-analyses, typical elements of meta-analyses, and basic statistical and analytic issues that arise, such as choice of meta-analytic model and different sources of variability and bias in estimates. The chapter closes with discussion of emerging issues in meta-analysis and directions for future research.