Epidemiology study design and data analysis 3rd edition By Mark Woodward, Mark Woodward ISBN 1439839706 9781439839706

Epidemiology study design and data analysis 3rd edition By Mark Woodward, Mark Woodward ISBN 1439839706 9781439839706

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ISBN 10: 1439839706
ISBN 13: 9781439839706
Author: Mark Woodward, Mark Woodward

Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems.

Epidemiology : study design and data analysis 3rd Table of contents:

FUNDAMENTAL ISSUES
What is Epidemiology?
Case Studies: The Work of Doll and Hill
Populations and Samples
Measuring Disease
Measuring the Risk Factor
Causality
Studies Using Routine Data
Study Design
Data Analysis
Exercises

BASIC ANALYTICAL PROCEDURES
Introduction
Case Study
Types of Variables
Tables and Charts
Inferential Techniques for Categorical Variables
Descriptive Techniques for Quantitative Variables
Inferences about Means
Inferential Techniques for Non-Normal Data
Measuring Agreement
Assessing Diagnostic Tests
Exercises

ASSESSING RISK FACTORS
Risk and Relative Risk
Odds and Odds Ratio
Relative Risk or Odds Ratio?
Prevalence Studies
Testing Association
Risk Factors Measured at Several Levels
Attributable Risk
Rate and Relative Rate
Measures of Difference
EPITAB Commands in Stata
Exercises

CONFOUNDING AND INTERACTION
Introduction
The Concept of Confounding
Identification of Confounders
Assessing Confounding
Standardization
Mantel-Haenszel Methods
The Concept of Interaction
Testing for Interaction
Dealing with Interaction
EPITAB Commands in Stata
Exercises

COHORT STUDIES
Design Considerations
Analytical Considerations
Cohort Life Tables
Kaplan-Meier Estimation
Comparison of Two Sets of Survival Probabilities
Competing Risk
The Person-Years Method
Period-Cohort Analysis
Exercises

CASE-CONTROL STUDIES
Basic Design Concepts
Basic Methods of Analysis
Selection of Cases
Selection of Controls
Matching
The Analysis of Matched Studies
Nested Case-Control Studies
Case-Cohort Studies
Case-Crossover Studies
Exercises

INTERVENTION STUDIES
Introduction
Ethical Considerations
Avoidance of Bias
Parallel Group Studies
Cross-Over Studies
Sequential Studies
Allocation to Treatment Group
Trials as Cohorts
Exercises

SAMPLE SIZE DETERMINATION
Introduction
Power
Testing a Mean Value
Testing a Difference between Means
Testing a Proportion
Testing a Relative Risk
Case-Control Studies
Complex Sampling Designs
Concluding Remarks
Exercises

MODELING QUANTITATIVE OUTCOME VARIABLES
Statistical Models
One Categorical Explanatory Variable
One Quantitative Explanatory Variable
Two Categorical Explanatory Variables
Model Building
General Linear Models
Several Explanatory Variables
Model Checking
Confounding
Splines
Panel Data
Non-Normal Alternatives
Exercises

MODELING BINARY OUTCOME DATA
Introduction
Problems with Standard Regression Models
Logistic Regression
Interpretation of Logistic Regression Coefficients
Generic Data
Multiple Logistic Regression Models
Tests of Hypotheses
Confounding
Interaction
Dealing with a Quantitative Explanatory Variable
Model Checking
Measurement Error
Case-Control Studies
Outcomes with Several Levels
Longitudinal Data
Binomial Regression
Propensity Scoring
Exercises

MODELING FOLLOW-UP DATA
Introduction
Basic Functions of Survival Time
Estimating the Hazard Function
Probability Models
Proportional Hazards Regression Models
The Cox Proportional Hazards Model
The Weibull Proportional Hazards Model
Model Checking
Competing Risk
Poisson Regression
Pooled Logistic Regression
Exercises

META-ANALYSIS
Reviewing Evidence
Systematic Review
A General Approach to Pooling
Investigating Heterogeneity
Pooling Tabular Data
Individual Participant Data
Dealing with Aspects of Study Quality
Publication Bias
Advantages and Limitations of Meta-Analysis
Exercises

RISK SCORES AND CLINICAL DECISION RULES
Introduction
Association and Prognosis
Risk Scores from Statistical Models
Quantifying Discrimination
Calibration
Recalibration
The Accuracy of Predictions
Assessing an Extraneous Prognostic Variable
Reclassification
Validation
Presentation of Risk Scores
Impact Studies
Exercises

COMPUTER-INTENSIVE METHODS
Rationale
The Bootstrap
Bootstrap Confidence Intervals
Practical Issues When Bootstrapping
Further Examples of Bootstrapping
Bootstrap Hypothesis Testing
Limitations of Bootstrapping
Permutation Tests
Missing Values
Naive Imputation Methods
Univariate Multiple Imputation
Multivariate Multiple Imputation
When Is It Worth Imputing?
Exercises

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