This text provides the first-ever compilation of bias analysis methods for use with
epidemiologic data. It guides the reader through the planning stages of bias analysis
including the design of validation studies and the collection of validity data from other
sources. Three chapters present methods for corrections to address selection bias uncontrolled
confounding and classification errors. Subsequent chapters extend these methods to
multidimensional bias analysis probabilistic bias analysis and multiple bias analysis. The
text concludes with a chapter on presentation and interpretation of bias analysis results.
Although techniques for bias analysis have been available for decades these methods are
considered difficult to implement. This text not only gathers the methods into one cohesive and
organized presentation it also explains the methods in a consistent fashion and provides
customizable spreadsheets to implement the solutions. By downloading the spreadsheets
(available at links provided in the text) readers can follow the examples in the text and then
modify the spreadsheet to complete their own bias analyses. Readers without experience using
quantitative bias analysis will be able to design implement and understand bias analyses that
address the major threats to the validity of epidemiologic research. More experienced analysts
will value the compilation of bias analysis methods and links to software tools that facilitate
their projects. Timothy L. Lash is an Associate Professor of Epidemiology and Matthew P. Fox is
an Assistant Professor in the Center for International Health and Development both at the
Boston University School of Public Health. Aliza K. Fink is a Project Manager at Macro
International in Bethesda Maryland. Together they have organized and presented many day-long
workshops on the methods of quantitative bias analysis. In addition they have collaborated on
many papers that developed methods of quantitative bias analysis or used the methods in the
data analysis.
