Measurement error and misclassificaion in statistics and epidemiology : impacts and Bayesian adjustments /
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Author / Creator: | Gustafson, Paul, 1968- |
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Imprint: | Boca Raton : Chapman & Hall/CRC, c2004. |
Description: | x, 188 p. : ill. ; 25 cm. |
Language: | English |
Subject: | |
Format: | Print Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/5054063 |
Table of Contents:
- Preface
- Guide to Notation
- 1. Introduction
- 1.1. Examples of Mismeasurement
- 1.2. The Mismeasurement Phenomenon
- 1.3. What is Ahead?
- 2. The Impact of Mismeasured Continuous Variables
- 2.1. The Archetypical Scenario
- 2.2. More General Impact
- 2.3. Multiplicative Measurement Error
- 2.4. Multiple Mismeasured Predictors
- 2.5. What about Variability and Small Samples?
- 2.6. Logistic Regression
- 2.7. Beyond Nondifferential and Unbiased Measurement Error
- 2.8. Summary
- 2.9. Mathematical Details
- 3. The Impact of Mismeasured Categorical Variables
- 3.1. The Linear Model Case
- 3.2. More General Impact
- 3.3. Inferences on Odds-Ratios
- 3.4. Logistic Regression
- 3.5. Differential Misclassification
- 3.6. Polychotomous Variables
- 3.7. Summary
- 3.8. Mathematical Details
- 4. Adjusting for Mismeasured Continuous Variables
- 4.1. Posterior Distributions
- 4.2. A Simple Scenario
- 4.3. Nonlinear Mixed Effects Model: Viral Dynamics
- 4.4. Logistic Regression I: Smoking and Bladder Cancer
- 4.5. Logistic Regression II: Framingham Heart Study
- 4.6. Issues in Specifying the Exposure Model
- 4.7. More Flexible Exposure Models
- 4.8. Retrospective Analysis
- 4.9. Comparison with Non-Bayesian Approaches
- 4.10. Summary
- 4.11. Mathematical Details
- 5. Adjusting for Mismeasured Categorical Variables
- 5.1. A Simple Scenario
- 5.2. Partial Knowledge of Misclassification Probabilities
- 5.3. Dual Exposure Assessment
- 5.4. Models with Additional Explanatory Variables
- 5.5. Summary
- 5.6. Mathematical Details
- 6. Further Topics
- 6.1. Dichotomization of Mismeasured Continuous Variables
- 6.2. Mismeasurement Bias and Model Misspecification Bias
- 6.3. Identifiability in Mismeasurement Models
- 6.4. Further Remarks
- Appendix. Bayes-MCMC Inference
- A.1. Bayes Theorem
- A.2. Point and Interval Estimates
- A.3. Markov Chain Monte Carlo
- A.4. Prior Selection
- A.5. MCMC and Unobserved Structure
- References
- Index