Survey research involves asking people to remember past events. Four biases occur when one asks people to recall past events in the presence of current information: hindsight bias, telescoping bias, anchoring and adjustment bias and implicit theory of change bias. This paper conducts a narrative review summarizing empirical research findings on the four sources of bias in self-reporting. The review provides an up-to-date summary of this research from 54 studies. It shows that the four biases exist and have fairly long research histories, the biases can be moderated by certain variables, they have negative effects and the clarification of the processes underlying each bias occurred gradually and continues. The review also shows the importance of using an integrative framework in the development of methods to minimize the effects of the four biases as each bias never occurs alone.

Bias analysis quantifies the influence of systematic error on an epidemiology study’s estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.

Healthcare decision makers in search of reliable information that compares health interventions increasingly turn to systematic reviews for the best summary of the evidence. Systematic reviews identify, select, assess, and synthesize the findings of similar but separate studies, and can help clarify what is known and not known about the potential benefits and harms of drugs, devices, and other healthcare services. Systematic reviews can be helpful for clinicians who want to integrate research findings into their daily practices, for patients to make well-informed choices about their own care, for professional medical societies and other organizations that develop clinical practice guidelines. Too often systematic reviews are of uncertain or poor quality. There are no universally accepted standards for developing systematic reviews leading to variability in how conflicts of interest and biases are handled, how evidence is appraised, and the overall scientific rigor of the process. In Finding What Works in Health Care the Institute of Medicine (IOM) recommends 21 standards for developing high-quality systematic reviews of comparative effectiveness research. The standards address the entire systematic review process from the initial steps of formulating the topic and building the review team to producing a detailed final report that synthesizes what the evidence shows and where knowledge gaps remain. Finding What Works in Health Care also proposes a framework for improving the quality of the science underpinning systematic reviews. This book will serve as a vital resource for both sponsors and producers of systematic reviews of comparative effectiveness research.

This edition is the most updated since its inception, is the essential text for students and professionals working in and around epidemiology or using its methods. It covers subject areas - genetics, clinical epidemiology, public health practice/policy, preventive medicine, health promotion, social sciences and methods for clinical research.

First edition published in 2002. Second edition published in 2008.

This book, first published in 2002, compiles psychologists' best attempts to answer important questions about intuitive judgment.