000			05485nam a22003377a 4500
001			20241106214626.0
003			OCoLC
005			20241106215044.0
008			241106b |||||||| |||| 00| 0 eng d
020			_a978-3-030-82672-7
020			_a 978-3-030-82673-4 (eBook)
022			_a 1431-8776
022			_a2197-5671 (electronic)
040			_cddc
041			_aEnglish
100			_qMatthew P. Fox
222			_aApplying Quantitative Bias Analysis to Epidemiologic Data. _badjusted antidepressant assess beta distribution bias analysis methods bias analysis results bias model bias parameters biases birth certificate breast cancer calculate case-control study Chap classification errors confidence interval controls corrected estimate covariate crude disease status educated guesses Epidemiol epidemiologic equals equations estimate of association example expected exposed exposure and disease exposure classification exposure misclassification exposure prevalence exposure status Fig frequentist Greenland heuristic HIV impact inference internal validation investigator loss-to-follow-up male circumcision measured median melanoma multidimensional bias analysis multiple bias analysis Muslim nondifferential misclassification nonparticipants nonrandomized null observed data odds ratio outcome participation predictive values probabilistic bias analysis probability density probability distribution quantitative bias analysis random error range risk ratio RR sample selection bias self-report sensitivity and specificity simple bias analysis simulation interval smoking status source population study population study’s substudy systematic error Table Total trapezoidal distribution uncertainty unexposed uniform distribution unmeasured confounder uveal melanoma validation data values assigned
240			_aApplying Quantitative Bias Analysis to Epidemiologic Data.
245			_aApplying Quantitative Bias Analysis to Epidemiologic Data.
250			_a2nd. Edition
260			_aDepartment of Epidemiology Boston University School of Public Health Boston, MA, USA | _bSpringer Nature Switzerland AG | _c2021.
300			_a475 Pages
300			_aIncludes References and Index
490			_aStatistics for Biology and Health
520			_aThis 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.
600			_xBiometry, Diseases, Epidemiology, Mathematics / Probability & Statistics / General, Medical / Biostatistics, Medical / Epidemiology, Medical / General, Medical / Infectious Diseases, Medical / Instruments & Supplies, Medical / Public Health, Medical informatics, Public health, Social Science / Methodology, Social Science / Research, Sociology—Methodology, Bias (Epidemiology), Computers / Computer Simulation, Computers / General, Electronic books, Epidemiologic Methods, Epidemiology -- Research -- Methodology, Epidemiology -- Research -- Statistical methods -- Methodology, Mathematics / General, Medical / Diseases, Medical / Informatics, Social Science / Sociology / General, Computer simulation, Digital computer simulation, Emerging infectious diseases, Epidemiology -- Research, Epidemiology -- Research -- Statistical methods, Medical care, Medicine, Public Health/Gesundheitswesen, Social sciences -- Methodology, Statistics, Statistics for Life Sciences, Medicine, Health Sciences.
700			_qRichard F. MacLehose
700			_qTimothy L. Lash
856			_uhttps://doi.org/10.1007/978-3-030-82673-4
942			_2ddc _cEB _n0
999			_c29700 _d29700