Evaluating the strength or persuasiveness of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. There are a myriad of potential biases to consider, but little guidance about how to asses the likely impact on study results. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of epidemiologic research in order to better evaluate it successes and limitations. The focus throughout is on practical tools for making optimal use of available data to assess whether hypothesized biases are operative and to anticipate concerns at the point of study design in order to ensure that needed information is generated. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated. The potential value of each approach as well as its limitations are discussed, using examples from the published literature. Such information should help those who generate and interpret epidemiologic research to apply methodological principles more effectively to substantive issues, leading to a more accurate appraisal of the current evidence and greater clarity about research needs.
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Evaluating the strength or persuasiveness of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. There is a myriad of potential biases to consider, but little guidance about how to assess the likely impact on study results. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of epidemiologic research in order to better evaluate its successes and limitations. The focus throughout is on practical tools for making optimal use of available data to assess whether hypothesised biases are operative and to anticipate concerns at the point of study design in order to ensure that needed information is generated. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated. The potential value of each approach as well as its limitations are discussed, using examples from the published literature. Such information should help those who generate and interpret epidemiologic research to apply methodological principles more effectively to substantive issues, leading to a more accurate appraisal of the current evidence and greater clarity about research needs.
This attractively presented book is extremely useful for professionals and graduate students doing or evaluating epidemiologic research. I have not seen another book like this one that so successfully integrates content and experience. The author has assembled a book that is necessary and essential reading for all those involved in interpreting epidemiologic evidence. (Doody's Journal)
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