By Timothy L. Lash
This textual content offers the first-ever compilation of bias research equipment to be used with epidemiologic information. It courses the reader in the course of the making plans phases of bias research, together with the layout of validation reports and the gathering of validity info from different resources. 3 chapters current tools for corrections to deal with choice bias, out of control confounding, and category blunders. next chapters expand those the right way to multidimensional bias research, probabilistic bias research, and a number of bias research. The textual content concludes with a bankruptcy on presentation and interpretation of bias research results.
Although strategies for bias research were on hand for many years, those equipment are thought of tough to enforce. this article not just gathers the tools into one cohesive and arranged presentation, it additionally explains the equipment in a constant model and offers customizable spreadsheets to enforce the recommendations. via downloading the spreadsheets (available at hyperlinks supplied within the text), readers can persist with the examples within the textual content after which adjust the spreadsheet to accomplish their very own bias analyses. Readers with out adventure utilizing quantitative bias research can be capable of layout, enforce, and comprehend bias analyses that deal with the foremost threats to the validity of epidemiologic learn. more matured analysts will worth the compilation of bias research equipment and hyperlinks to software program instruments that facilitate their projects.
Timothy L. Lash is an affiliate Professor of Epidemiology and Matthew P. Fox is an Assistant Professor within the heart for overseas overall healthiness and improvement, either on the Boston collage tuition of Public overall healthiness. Aliza ok. Fink is a venture supervisor at Macro overseas in Bethesda, Maryland. jointly they've got prepared and provided many day-long workshops at the equipment of quantitative bias research. moreover, they've got collaborated on many papers that built tools of quantitative bias research or used the equipment within the facts research.
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Extra resources for Applying Quantitative Bias Analysis to Epidemiologic Data
These were the bias parameters used to address misclassification. 2). Conditional on the accuracy of the distributions assigned to the bias parameters, this probabilistic bias analysis (which only accounts for one source of bias) supports the notion that the result is unlikely to arise from a bias toward the null induced Quantifying Error 31 by nondifferential nondependent misclassification of the dichotomous exposure variable, because the central tendency remained near null and the interval remained narrow.
This consideration should immediately suggest the quantitative analyses that will explore these threats, and should thereby inform the data collection that will be required to complete the quantitative analyses. For example, an investigator may design a retrospective case-control study of the relation between leisure exposure to sunlight and the occurrence of melanoma. Cases of melanoma and controls sampled from the source population will be interviewed by telephone regarding their exposures to sunlight and other risk factors for melanoma.
Lash et al. 1007/978-0-387-87959-8_3, © Springer Science + Business Media, LLC 2009 33 34 3 Data Sources for Bias Analysis the values to assign to bias parameters and satisfies the assumptions of empirical methods, then these empirical methods of bias analysis may be preferable to the methods described in this text (see Chap. 1). Selection Bias When some eligible participants refuse to participate in a study, the nonparticipation may introduce a selection bias. In particular, if the proportion of participants depends on both exposure and disease status, then the conventional estimate of association would be biased (other scenarios would also introduce selection bias, as described in Chap.