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[null,"1.","Record Nr.",null,"UNINA9910556891103321"]
[null,null,"Autore",null,"Lash Timothy L."]
[null,null,"Titolo",null,"Applying quantitative bias analysis to epidemiologic data / / Matthew P. Fox, Richard F. MacLehose, and Timothy L. Lash"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2022]"]
[{"$nulls":4},"©2022"]
[null,null,"ISBN",null,"3-030-82673-2"]
[null,null,"Edizione",null,"[Second edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (475 pages)"]
[null,null,"Collana",null,"Statistics for Biology and Health"]
[null,null,"Disciplina",null,"614.4072"]
[null,null,"Soggetti",null,"Epidemiology - Research"]
[{"$nulls":4},"Social sciences - Methodology"]
[{"$nulls":4},"Epidemiologia"]
[{"$nulls":4},"Estadística matemàtica"]
[{"$nulls":4},"Llibres electrònics"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: Introduction, Objectives, and an Alternative -- Introduction: Biases in Health Research -- Statistical Inference in Public Health Research -- The Treatment of Uncertainty in Nonrandomized Research -- When Bias Analysis Will Be Most Useful -- Judgments Under Uncertainty -- The Dual-Process Model of Cognition -- Anchoring and Adjustment -- Overconfidence -- Failure to Account for the Base-Rate -- Conclusion -- References -- Chapter 2: A Guide to Implementing Quantitative Bias Analysis -- Introduction -- Reducing Error -- Reducing Error by Design -- Reducing Error in the Analysis -- Quantifying Error -- Evaluating the Potential Value of Quantitative Bias Analysis? -- Planning for Bias Analysis -- Creating a Data Collection Plan for Bias Analysis -- Creating an Analytic Plan for a Bias Analysis -- Type of Data: Record-Level Versus Summary -- Type of Bias Analysis -- Order of Bias Analysis Adjustments -- Bias Analysis Techniques -- Simple Bias Analysis -- Multidimensional Bias Analysis -- Probabilistic Bias Analysis -- Multiple Bias Modeling -- Direct Bias Modeling and Missing Data Methods -- Bayesian Bias Analysis -- Assigning Values and Distributions to Bias Parameters -- Directed Acyclic Graphs -- Conclusion -- References -- Chapter 3: Data Sources for Bias Analysis -- Bias Parameters -- Internal Data Sources -- Selection Bias -- Uncontrolled Confounding -- "]
[{"$nulls":4},"Information Bias -- Design of Internal Validation Studies -- Limitations of Internal Validation Studies -- External Data Sources -- Selection Bias -- Unmeasured Confounder -- Information Bias -- Expert Opinion -- Summary -- References -- Chapter 4: Selection Bias -- Introduction -- Definitions and Terms -- Conceptual -- Depicting Selection Bias Using Causal Graphs -- Design Considerations -- Bias Analysis."]
[{"$nulls":4},"Motivation for Bias Analysis -- Sources of Data -- Simple Bias-Adjustment for Differential Initial Participation -- Example -- Introduction to Bias Analysis -- Bias Analysis by Projecting the Exposed Proportion Among Nonparticipants -- Bias Analysis Using Selection Proportions -- Bias Analysis Using Inverse Probability of Participation Weighting -- Simple Bias-Adjustment for Differential Loss-to-Follow-up -- Example -- Bias Analysis by Modeling Outcomes -- Bias Analysis by Inverse Probability of Attrition Weighting -- Multidimensional Bias Analysis for Selection Bias -- Example -- References -- Chapter 5: Uncontrolled Confounders -- Introduction -- Key Concepts -- Definitions -- Motivation for Bias Analysis -- Data Sources -- Introduction to Simple Bias Analysis -- Approach -- Introduction to the Example -- Bias Parameters -- Implementation of Simple Bias Analysis -- Ratio Measures -- Example -- Difference Measures -- Person-time Designs -- Unmeasured Confounder in the Presence of Effect Measure Modification -- Polytomous Confounders -- Multidimensional Bias Analysis for Unmeasured Confounding -- Example -- Bounding the Bias Limits of an Unmeasured Confounding -- Analytic Approach -- The E-Value and G-Value -- Signed Directed Acyclic Graphs to Estimate the Direction of Bias -- References -- Chapter 6: Misclassification -- Introduction -- Definitions and Terms -- Differential vs. Nondifferential Misclassification -- Dependent vs. Independent Misclassification -- Directed Acyclic Graphs and Misclassification -- Calculating Classification Bias Parameters from Validation Data -- Sources of Data -- Bias Analysis of Exposure Misclassification -- Bias-Adjusting for Exposure Misclassification Using Sensitivity and Specificity: Nondifferential and Independent Errors -- Bias-Adjusting for Exposure Misclassification Using Predictive Values."]
[{"$nulls":4},"Bias-Adjustment for Nondifferential Outcome Misclassification Using Positive Predictive Values for the Risk Ratio Measure of A... -- Bias-Adjustments Using Sensitivity and Specificity: Differential Independent Errors -- Bias-Adjustments Using Sensitivity and Specificity: Internal Validation Data -- Overreliance on Nondifferential Misclassification Biasing Toward the Null -- Disease Misclassification -- Bias-Adjustments with Sensitivity and Specificity: Nondifferential and Independent Errors -- Disease Misclassification in Case-Control Studies -- Overreliance on Nondifferential Misclassification Biasing Toward the Null -- Covariate Misclassification -- Bias-Adjustments with Sensitivity and Specificity: Nondifferential and Differential Misclassification with Independent Errors -- Overreliance on Nondifferential Misclassification of Covariates Biasing Toward the Null -- Dependent Misclassification -- Matrix Method for Misclassification Adjustment -- Multidimensional Bias Analysis for Misclassification -- Limitations -- Negative Expected Cell Frequencies -- Other Considerations -- References -- Chapter 7: Preparing for Probabilistic Bias Analysis -- Introduction -- Preparing for Probabilistic Bias Analysis -- Statistical Software for Probabilistic Bias Analysis -- Summary Level Versus Record Level Probabilistic Bias Analysis -- Describing Uncertainty in the Bias Parameters -- Probability Distributions -- Uniform Distribution -- Generalized Method for Sampling from Distributions -- Trapezoidal Distribution -- Triangular Distribution -- Normal Distribution -- Beta Distribution -- Bernoulli and Binomial Distributions -- Other Probability Distributions -- "]
[{"$nulls":4},"Sensitivity to Chosen Distributions -- Correlated Distributions -- Conclusions -- References -- Chapter 8: Probabilistic Bias Analysis for Simulation of Summary Level Data -- Introduction."]
[{"$nulls":4},"Analytic Approach for Summary Level Probabilistic Bias Analysis -- Exposure Misclassification Implementation -- Step 1: Identify the Source of Bias -- Step 2: Select the Bias Parameters -- Step 3: Assign Probability Distributions to Each Bias Parameter -- Step 4: Use Simple Bias Analysis Methods to Incorporate Uncertainty in the Bias Parameters and Random Error -- Step 4a: Sample from the Bias Parameter Distributions -- Step 4b: Generate Bias-Adjusted Data Using Simple Bias Analysis Methods and the Sampled Bias Parameters -- Step 4c: Incorporate Conventional Random Error by Sampling Summary Statistics -- Step 4c (Alternate): Resample the Prevalence of Misclassification Adjusted Exposure -- Step 5: Save the Bias-Adjusted Estimate and Repeat Steps 4a-c -- Step 6: Summarize the Bias-Adjusted Estimates with a Frequency Distribution that Yields a Central Tendency and Simulation Inte... -- Misclassification Implementation: Predictive Values -- Misclassification Implementation: Predictive Values - Alternative -- Misclassification of Outcomes and Confounders -- Uncontrolled Confounding Implementation -- Step 1: Identify the Source of Bias -- Step 2: Identify the Bias Parameters -- Step 3: Assign Probability Distributions to Each Bias Parameter -- Step 4: Use Simple Bias Analysis Methods to Incorporate Uncertainty in the Bias Parameters and Random Error -- Step 4a: Sample from the Bias Parameter Distributions -- Step 4b: Generate Bias-Adjusted Data Using Simple Bias Analysis Methods and the Sampled Bias Parameters -- Step 4c: Sample the Bias-Adjusted Effect Estimate -- Steps 5 and 6: Resample, Save and Summarize -- Confounding Implementation Alternative: Relative Risk Due to Confounding -- Step 4: Use Simple Bias Analysis Methods to Incorporate Uncertainty in the Bias Parameters and Random Error -- Step 4a: Sample from the Bias Parameter Distributions."]
[{"$nulls":4},"Step 4b: Generate Bias-Adjusted Results Using Simple Bias Analysis Methods and the Sampled Bias Parameters -- Step 4c: Sample the Bias-Adjusted Effect Estimate -- Steps 5 and 6: Resample, Save and Summarize -- Selection Bias Implementation -- An Example of Probabilistic Bias Analysis in the Presence of Substantial Source Population Data -- Step 1: Identify the Source of Bias -- Step 2: Identify the Bias Parameters -- Step 3: Assign Probability Distributions to Each Bias Parameter -- Step 4: Use Simple Bias Analysis Methods to Incorporate Uncertainty in the Bias Parameters and Random Error -- Step 4a: Sample from the Bias Parameter Distributions -- Step 4b: Generate Bias-Adjusted Data Using Simple Bias Analysis Methods and the Sampled Bias Parameters -- Steps 4c: Sample the Bias-Adjusted Effect Estimate -- Steps 5 and 6: Resample, Save and Summarize -- Selection Bias Adjustment Using Selection Probabilities -- Step 1: Identify the Source of Bias -- Step 2: Identify the Bias Parameters -- Step 3: Assign Probability Distributions to Each Bias Parameter -- Step 4: Use Simple Bias Analysis Methods to Incorporate Uncertainty and Random Error -- Step 4a: Sample from the Bias Parameter Distributions -- Step 4b: Generate Bias-Adjusted Data Using Simple Bias Analysis Methods and the Sampled Bias Parameters -- Steps 4c: Sample the Bias-Adjusted Effect Estimate -- Steps 5 and 6: Resample, Save and Summarize -- Computing Issues with Summary Level Probabilistic Bias Analysis -- Bootstrapping -- Impossible Values for Bias Parameters and Model Diagnostic Plots -- Conclusions -- Appendix: Sampling Models for Exposure Misclassification -- References -- Chapter 9: Probabilistic Bias Analysis for Simulation of Record-Level Data -- Introduction -- Exposure Misclassification Implementation -- Step 1: Identify the "]
[{"$nulls":4},"Source of Bias -- Step 2: Select the Bias Parameters."]
[{"$nulls":4},"Step 3: Assign Probability Distributions to Each Bias Parameter."]
[null,"2.","Record Nr.",null,"UNINA9910958993503321"]
[null,null,"Titolo",null,"Ethics and images of pain / / edited by Asbjrn Grnstad and Henrik Gustafsson"]
[null,null,"Pubbl/distr/stampa",null,"New York, : Routledge, 2012"]
[{"$nulls":4},"New York : , : Routledge, , 2012"]
[null,null,"ISBN",null,"1-136-45305-9"]
[{"$nulls":4},"1-280-66119-4"]
[{"$nulls":4},"9786613638120"]
[{"$nulls":4},"1-136-45306-7"]
[{"$nulls":4},"0-203-12590-8"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (263 p.)"]
[null,null,"Collana",null,"Routledge advances in art and visual studies ; ; 1"]
[null,null,"Disciplina",null,"700.453"]
[{"$nulls":4},"700/.453"]
[{"$nulls":4},"701"]
[null,null,"Soggetti",null,"Art - Moral and ethical aspects"]
[{"$nulls":4},"Mass media - Moral and ethical aspects"]
[{"$nulls":4},"Pain in art"]
[{"$nulls":4},"Pain in mass media"]
[{"$nulls":4},"Pain in the performing arts"]
[{"$nulls":4},"Performing arts - Moral and ethical aspects"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Cover; Ethics and Images of Pain; Copyright; Contents; List of Figures; Acknowledgements; Preface; Introduction; PART I: From Voyeurism to Visual Politics; 1. Do Not Look at Y/Our Own Peril: Voyeurism as Ethical Necessity, or To See as a Child Again; 2. Associates in Crime and Guilt; 3. Painful Photographs: From the Ethics of Spectatorship to Visual Politics; PART II: Looking In, Looking Away; 4. The Violence of the Documentary Image: Errol Morris's Standard Operating Procedure"]
[{"$nulls":4},"5. Visual Irruptions, Mediated Suffering, and the Robert Dziekanski Tragedy: An Inquiry into the Effi cacy of the Image6. Tuning Out, Turning In, and Walking Off : The Film Spectator in Pain; PART III: Performances; 7. Imaging Pain; 8. The Unsettling Moment: On Mathilde ter Heijne's Suicide Trilogy; 9. Gulag Follies; PART IV: Mimetic and Mnemonic Frames; 10. Imag(in)ing Painful Pasts: Mimetic and Poetic "]
[{"$nulls":4},"Style in War Films; 11. The Sanctifi ed Fallen: The War Film as Witness; 12. Medical Horror: Visual Documents From the History of Lobotomy; Contributers; Index"]
[null,null,null,"Sommario/riassunto","Few phenomena are as formative of our experience of the visual world as displays of suffering. But what does it mean to have an ethical experience of disturbing or traumatizing images? What kind of ethical proposition does an image of pain mobilize? How may the spectator learn from and make use of the painful image as a source of ethical reflection? Engaging with a wide range of visual media--from painting, theatre, and sculpture, to photography, film, and video--this interdisciplinary collection of essays by leading and emerging scholars of visual culture offers a reappraisal of the increasin"]