1. 1Getting Started: The Anatomy and Physiology of Clinical Research
2. 2Conceiving the Research Question and Developing the Study Plan
3. 3Choosing the Study Participants: Specification, Sampling, and Recruitment
4. 4Planning the Measurements: Precision, Accuracy, and Validity
5. 5Getting Ready to Estimate Sample Size: Hypotheses and Underlying Principles
6. 6Estimating Sample Size: Applications and Examples
7. 7Addressing Ethical Issues
8. 8Designing Cross-Sectional and Cohort Studies
9. 9Designing Case-Control Studies
10. 10Estimating Causal Effects Using Observational Studies
11. 11Designing a Randomized Blinded Trial
12. 12Alternate Interventional Study Designs
13. 13Designing Studies of Medical Tests
14. 14Qualitative Approaches in Clinical Research
15. 15Community-Engaged Research
16. 16Research Using Existing Data or Specimens
17. 17Designing, Selecting, and Administering Self-Reported Measures
18. 18Study Implementation and Quality Control
19. 19Data Management
20. 20Writing a Proposal for Funding Research

Part I: Foundations

1. 1The Scope of Epidemiology
2. 2Causal Inference and Scientific Reasoning
3. 3Formal Causal Models
4. 4Measures of Occurrence
5. 5Measures of Effect and Measures of Association
6. 6Epidemiologic Study Design With Validity and Efficiency Considerations

Part II: Study Design and Interpretation

1. 7Cohort Studies
2. 8Case-Control Studies
3. 9Public Health Surveillance
4. 10Field Methods
5. 11Studies Relying on Secondary Data
6. 12Confounding and Confounders
7. 13Measurement and Measurement Error
8. 14Selection Bias and Generalizability
9. 15Precision and Study Size

Part III: Data Analysis

1. 16Fundamentals of Epidemiologic Data Analysis
2. 17Introduction to Categorical Statistics
3. 18Stratification and Standardization
4. 19Categorical Analysis of Polytomous Exposures and Outcomes
5. 20Regression Analysis Part I: Model Specification
6. 21Regression Analysis Part II: Model Fitting and Assessment
7. 22Time-to-Event Analysis
8. 23Introduction to Bayesian Statistics
9. 24Longitudinal and Cluster-Correlated Data Analysis
10. 25Causal Inference With Time-Varying Exposures
11. 26Analysis of Interaction
12. 27Mediation Analysis
13. 28Instrumental Variables and Quasi-Experimental Approaches
14. 29Bias Analysis
15. 30Ecologic Studies and Analysis
16. 31Agent-Based Modeling

Part IV: Special Topics

1. 32Infectious Disease Epidemiology
2. 33Reproductive Epidemiology
3. 34Psychiatric Epidemiology
4. 35Clinical Epidemiology
5. 36Molecular Epidemiology
6. 37Genetic Epidemiology
7. 38Injury and Violence Epidemiology
8. 39Social Epidemiology
9. 40Environmental Epidemiology
10. 41Occupational Epidemiology
11. 42Nutritional Epidemiology
12. 43Pharmacoepidemiology

Section I: The Epidemiologic Approach to Disease and Intervention

1. 1Introduction
2. 2The Dynamics of Disease Transmission
3. 3The Occurrence of Disease: I. Disease Surveillance and Measures of Morbidity
4. 4The Occurrence of Disease: II. Mortality and Other Measures of Disease Impact
5. 5Assessing the Validity and Reliability of Diagnostic and Screening Tests
6. 6The Natural History of Disease: Ways of Expressing Prognosis

Section II: Using Epidemiology to Identify the Cause of Disease

1. 7Observational Studies
2. 8Cohort Studies
3. 9Comparing Cohort and Case-Control Studies
4. 10Assessing Preventive and Therapeutic Interventions: Randomized Trials
5. 11Randomized Trials: Some Further Issues
6. 12Estimating Risk: Is There an Association?
7. 13More on Risk: Estimating the Potential for Prevention
8. 14From Association to Causation: Deriving Inferences From Epidemiologic Studies
9. 15More on Causal Inference: Bias, Confounding, and Interaction
10. 16Identifying the Roles of Genetic and Environmental Factors in Disease Causation

Section III: Applying Epidemiology to Evaluation and Policy

1. 17Using Epidemiology to Evaluate Health Services
2. 18Epidemiologic Approach to Evaluating Screening Programs
3. 19Epidemiology and Public Policy
4. 20Ethical and Professional Issues in Epidemiology

Part 1: Introduction

1. 1Basic Study Designs in Analytical Epidemiology

Part 2: Measures of Disease Occurrence and Association

1. 2Measuring Disease Occurrence
2. 3Measuring Associations Between Exposures and Outcomes

Part 3: Threats to Validity and Issues of Interpretation

1. 4Understanding Lack of Validity: Bias
2. 5Identifying Noncausal Associations: Confounding
3. 6Defining and Assessing Heterogeneity of Effects: Interaction

Part 4: Dealing With Threats to Validity

1. 7Stratification and Adjustment: Multivariate Analysis in Epidemiology
2. 8Quality Assurance and Control

Part 5: Issues of Reporting and Application of Epidemiologic Results

1. 9Communicating Results of Epidemiologic Studies
2. 10Epidemiologic Issues in the Interface With Public Health Policy

1. 1Introduction
2. 2Frequency
3. 3Abnormality
4. 4Diagnosis
5. 5Risk: Basic Principles
6. 6Risk: Exposure to Disease
7. 7Risk: From Disease to Exposure
8. 8Prognosis
9. 9Treatment
10. 10Prevention
11. 11Chance
12. 12Cause
13. 13Summarizing the Evidence
14. 14Knowledge Management

Part I: Causal Inference Without Models

1. 1A Definition of Causal Effect
2. 2Randomized Experiments
3. 3Observational Studies
4. 4Effect Modification
5. 5Interaction
6. 6Graphical Representation of Causal Effects
7. 7Confounding
8. 8Selection Bias
9. 9Measurement Bias
10. 10Random Variability

Part II: Causal Inference With Models

1. 11Why Model?
2. 12IP Weighting and Marginal Structural Models
3. 13Standardization and the Parametric G-Formula
4. 14G-Estimation of Structural Nested Models
5. 15Outcome Regression and Propensity Scores
6. 16Instrumental Variable Estimation
7. 17Causal Survival Analysis
8. 18Variable Selection for Causal Inference

Part III: Causal Inference From Complex Longitudinal Data

1. 19Time-Varying Treatments
2. 20Treatment-Confounder Feedback
3. 21G-Methods for Time-Varying Treatments
4. 22Target Trial Emulation
5. 23Causal Mediation

1. 1Introduction to Clinical Trials
2. 2Ethical Issues
3. 3What Is the Question?
4. 4Study Population
5. 5Basic Study Design
6. 6The Randomization Process
7. 7Blinding
8. 8Sample Size
9. 9Baseline Assessment
10. 10Recruitment of Study Participants
11. 11Data Collection and Quality Control
12. 12Assessment and Reporting of Harm
13. 13Assessment of Health Related Quality of Life
14. 14Participant Adherence
15. 15Survival Analysis
16. 16Monitoring Committee Structure and Function
17. 17Statistical Methods Used in Interim Monitoring
18. 18Issues in Data Analysis
19. 19Closeout
20. 20Reporting and Interpreting of Results
21. 21Multicenter Trials
22. 22Regulatory Issues

Part A: The Foundations

1. ·Using the medical literature; what is evidence-based medicine; asking questions; finding current best evidence; why study results mislead (bias and random error)

Part B: Therapy

1. ·Randomised trials, understanding results, confidence intervals, non-inferiority, subgroup and composite end points

Part C: Harm (Observational Studies)

1. ·Cohort and case-control studies of harm, correlation and causation

Part D: Diagnosis

1. ·The process of diagnosis, differential diagnosis, diagnostic tests and clinical prediction rules

Part E: Prognosis

1. ·Studies of prognosis and their application

Part F: Summarizing the Evidence

1. ·Systematic reviews, meta-analysis, network meta-analysis and confidence in estimates (GRADE)

Part G: Moving From Evidence to Action

1. ·Clinical practice guidelines, decision making, shared decision making and how to teach EBM

1. 1Introduction
2. 2Asking Answerable Clinical Questions
3. 3Acquiring the Evidence: How to Find Current Best Evidence and Have Current Best Evidence Find Us
4. 4Appraising the Evidence
5. 5Therapy
6. 6Diagnosis and Screening
7. 7Prognosis
8. 8Harm
9. 9Evaluation
10. 10Teaching EBM

1. 1Why Read Papers at All?
2. 2Searching the Literature
3. 3Getting Your Bearings: What Is This Paper About?
4. 4Assessing Methodological Quality
5. 5Statistics for the Non-Statistician
6. 6Papers That Report Clinical Trials of Simple Interventions
7. 7Papers That Report Trials of Complex Interventions
8. 8Papers That Report Diagnostic or Screening Tests
9. 9Papers That Summarise Other Papers (Systematic Reviews and Meta-Analyses)
10. 10Papers That Advise You What to Do (Guidelines)
11. 11Papers That Estimate What Things Cost (Health Economic Evaluations)
12. 12Papers That Go Beyond Numbers (Qualitative Research)
13. 13Papers That Report Questionnaire Research
14. 14Papers That Report Quality Improvement Case Studies
15. 15Papers That Describe Genetic Association Studies
16. 16Applying Evidence With Patients
17. 17Papers on Artificial Intelligence in Healthcare
18. 18EBM+: The Importance of Mechanistic Evidence
19. 19Papers That Report Consensus Exercises
20. 20Criticisms of Evidence-Based Healthcare

Part One: Core Methods

1. 1Starting a Review
2. 2Determining the Scope of the Review and the Questions It Will Address
3. 3Defining the Criteria for Including Studies and How They Will Be Grouped for the Synthesis
4. 4Searching for and Selecting Studies
5. 5Collecting Data
6. 6Choosing Effect Measures and Computing Estimates of Effect
7. 7Considering Bias and Conflicts of Interest Among the Included Studies
8. 8Assessing Risk of Bias in a Randomized Trial
9. 9Summarizing Study Characteristics and Preparing for Synthesis
10. 10Analysing Data and Undertaking Meta-Analyses
11. 11Undertaking Network Meta-Analyses
12. 12Synthesizing and Presenting Findings Using Other Methods
13. 13Assessing Risk of Bias Due to Missing Results in a Synthesis
14. 14Completing 'Summary of Findings' Tables and Grading the Certainty of the Evidence
15. 15Interpreting Results and Drawing Conclusions

Part Two: Specific Perspectives in Reviews

1. 16Equity and Specific Populations
2. 17Intervention Complexity
3. 18Patient-Reported Outcomes
4. 19Adverse Effects
5. 20Economic Evidence
6. 21Qualitative Evidence

Part Three: Further Topics

1. 22Prospective Approaches to Accumulating Evidence
2. 23Including Variants on Randomized Trials
3. 24Including Non-Randomized Studies on Intervention Effects
4. 25Assessing Risk of Bias in a Non-Randomized Study
5. 26Individual Participant Data

1. 1Systematic Reviews in Health Research: An Introduction

Part I: Principles and Procedures

1. 2Principles of Systematic Reviewing
2. 3Identifying Randomized Controlled Trials
3. 4Assessing the Risk of Bias in Randomized Trials
4. 5Investigating and Dealing with Publication Bias and Other Reporting Biases
5. 6Managing People and Data
6. 7Reporting and Appraisal of Systematic Reviews

Part II: Meta-Analysis

1. 8Effect Measures
2. 9Combining Results Using Meta-Analysis
3. 10Exploring Heterogeneity
4. 11Dealing with Missing Outcome Data in Meta-Analysis
5. 12Individual Participant Data Meta-Analysis
6. 13Network Meta-Analysis
7. 14Dose-Response Meta-Analysis

Part III: Specific Study Designs

1. 15Systematic Reviews of Nonrandomized Studies of Interventions
2. 16Systematic Reviews of Diagnostic Accuracy
3. 17Systematic Reviews of Prognostic Factor Studies
4. 18Systematic Reviews of Prediction Models
5. 19Systematic Reviews of Epidemiological Studies of Etiology and Prevalence
6. 20Meta-Analysis in Genetic Association Studies

Part IV: Cochrane and Guideline Development

1. 21Cochrane: Trusted Evidence. Informed Decisions. Better Health
2. 22Using Systematic Reviews in Guideline Development: The GRADE Approach

Part V: Outlook

1. 23Innovations in Systematic Review Production
2. 24Future for Systematic Reviews and Meta-Analysis

Part VI: Software

1. 25Meta-Analysis in Stata
2. 26Meta-Analysis in R
3. 27Comprehensive Meta-Analysis Software

Chapter 1

1. ·Making the case for evidence-based practice and cultivating a spirit of inquiry

Chapters 2-3

1. ·Asking compelling clinical questions (PICOT) and finding relevant evidence

Chapters 4-7

1. ·Critically appraising knowledge; integrating clinical expertise and patient preferences; appraising quantitative, qualitative and mixed-methods evidence

Chapter 8

1. ·Using robust clinical practice guidelines

Chapters 9-11, 14-15

1. ·Implementation strategies, quality improvement, implementation competencies, models and implementation science

Chapters 12-13, 16-17

1. ·Leadership for evidence-based organisations, innovation, mentoring and motivating change

Chapters 18-19

1. ·Teaching evidence-based practice in academic and clinical settings

Chapters 20-23

1. ·Evidence and policy, disseminating evidence, generating evidence through research, writing grant proposals

Chapter 24

1. ·Ethical considerations for implementing and generating evidence

Part 1: Foundations of Nursing Research and Evidence-Based Practice

1. 1Introduction to Nursing Research in an Evidence-Based Practice Environment
2. 2Evidence-Based Nursing: Translating Research Evidence into Practice
3. 3Key Concepts and Steps in Qualitative and Quantitative Research

Part 2: Conceptualizing and Planning a Study

1. 4Research Problems, Research Questions, and Hypotheses
2. 5Literature Reviews: Finding and Critically Appraising Evidence
3. 6Theoretical Frameworks
4. 7Ethics in Nursing Research
5. 8Planning a Nursing Study

Part 3: Designing and Conducting Quantitative Studies

1. 9Quantitative Research Design
2. 10Rigor and Validity in Quantitative Research
3. 11Specific Types of Quantitative Research
4. 12Quality Improvement and Improvement Science
5. 13Sampling in Quantitative Research
6. 14Data Collection in Quantitative Research
7. 15Measurement and Data Quality
8. 16Developing and Testing Self-Report Scales
9. 17Descriptive Statistics
10. 18Inferential Statistics
11. 19Multivariate Statistics
12. 20Processes of Quantitative Data Analysis
13. 21Clinical Significance and Interpretation of Quantitative Results

Part 4: Designing and Conducting Qualitative Studies

1. 22Qualitative Research Design and Approaches
2. 23Sampling in Qualitative Research
3. 24Data Collection in Qualitative Research
4. 25Qualitative Data Analysis
5. 26Trustworthiness and Rigor in Qualitative Research

Part 5: Designing and Conducting Mixed Methods Studies

1. 27Basics of Mixed Methods Research
2. 28Developing Complex Nursing Interventions Using Mixed Methods Research
3. 29Feasibility and Pilot Studies of Interventions Using Mixed Methods

Part 6: Building an Evidence Base for Nursing Practice

1. 30Systematic Reviews of Research Evidence
2. 31Applicability, Generalizability, and Relevance: Toward Practice-Based Evidence
3. 32Disseminating Evidence: Reporting Research Findings
4. 33Writing Proposals to Generate Evidence

Unit 1: Introduction to Nursing Research

1. 1Discovering the World of Nursing
2. 2Evolution of Research in Building Evidence-Based Nursing Practice
3. 3Introduction to Quantitative Research
4. 4Introduction to Qualitative Research

Unit 2: The Research Process

1. 5Research Problem and Purpose
2. 6Objectives, Questions, Hypotheses, and Study Variables
3. 7Review of Relevant Literature
4. 8Frameworks
5. 9Ethics in Research
6. 10Quantitative Methodology: Noninterventional Designs and Methods
7. 11Quantitative Methodology: Interventional Designs and Methods
8. 12Qualitative Research Methods
9. 13Outcomes Research
10. 14Mixed Methods Research
11. 15Sampling
12. 16Quantitative Measurement Concepts
13. 17Measurement Methods Used in Developing Evidence-Based Practice

Unit 3: Putting It All Together for Evidence-Based Health Care

1. 18Critical Appraisal of Nursing Studies
2. 19Evidence Synthesis and Strategies for Implementing and Sustaining Evidence-Based Practice

Unit 4: Collecting and Analyzing Data, Determining Findings, and Disseminating Research

1. 20Collecting and Managing Data
2. 21Introduction to Statistical Analysis
3. 22Using Statistics to Describe Variables
4. 23Using Statistics to Examine Relationships
5. 24Using Statistics to Predict
6. 25Using Statistics to Determine Differences
7. 26Interpreting Research Outcomes
8. 27Disseminating Research Findings

Unit 5: Proposing and Seeking Funding for Research

1. 28Writing Research Proposals and Seeking Funding

Section I: Investigating Health Services and Health: The Scope of Research

1. 1Evaluating health services: multidisciplinary collaboration
2. 2Social research on health: sociological and psychological concepts and approaches
3. 3Quality of life: concepts, measurements and patient perception
4. 4Health needs and their assessment: demography and epidemiology
5. 5Costing health services: health economics

Section II: The Philosophy, Theory and Practice of Research

1. 6The philosophical framework of measurement
2. 7The principles of research

Section III: Quantitative Research: Sampling and Research Methods

1. 8Sample size and sampling for quantitative and qualitative research
2. 9Quantitative research: surveys
3. 10Quantitative research: experiments and other analytic methods of investigation
4. 11Sample selection and group assignment methods in experiments and other analytic methods

Section IV: The Tools of Quantitative Research

1. 12Data collection methods in quantitative research: questionnaires, interviews and their response rates
2. 13Questionnaire design
3. 14Techniques of survey interviewing
4. 15Preparation of quantitative data for coding and analysis

Section V: Qualitative and Mixed Research Methods

1. 16Unstructured and structured observational studies
2. 17Unstructured interviewing
3. 18Focus groups
4. 19Mixed research approaches

1. 1Scientific Foundations of Health Services Research
2. 2Conceptualizing Health Services Research
3. 3Groundwork in Health Services Research
4. 4Research Review
5. 5Secondary Analysis
6. 6Qualitative Research
7. 7Experimental Research
8. 8Survey Research
9. 9Evaluation Research
10. 10Design a Health Services Research Study
11. 11Sampling in Health Services Research
12. 12Measurements in Health Services Research
13. 13Data Collection and Processing in Health Services Research
14. 14Statistical Analysis in Health Services Research
15. 15Applying Health Services Research

1. 1Introduction
2. 2The Role of Theory in Qualitative Research
3. 3Ethical Issues in Qualitative Research
4. 4Interviews
5. 5Focus Groups
6. 6Observational Methods
7. 7Documentary Analysis
8. 8Digital Data and Online Qualitative Research
9. 9Analysis
10. 10Conversation Analysis
11. 11Synthesising Qualitative Research
12. 12Mixed Methods Research
13. 13Case Studies
14. 14Participatory Research in Health Care
15. 15Quality in Qualitative Research

Part 1: Principles and Approaches in Qualitative Health Research

1. 1Qualitative Methodology in Health
2. 2The Role of Theory
3. 3Developing Research Proposals
4. 4Responsibilities, Ethics and Values

Part 2: Generating Data

1. 5Interviews
2. 6Group Interviews and Discussions
3. 7Ethnographic and Observational Methods
4. 8Using Secondary Sources

Part 3: Managing and Analysing Data

1. 9Beginning Data Analysis
2. 10Developing Qualitative Analysis

Part 4: Qualitative Research in Practice

1. 11Integrating Methods and Disciplines
2. 12Reading, Appraising and Reviewing
3. 13Synthesizing Qualitative Evidence
4. 14Knowledge Exchange and Dissemination

Part I: Mixed Methods 101

1. 1Definition and Overview of Mixed Methods Designs
2. 2Applications and Illustrations of Mixed Methods Health Sciences Research
3. 3Determining the Appropriateness and Feasibility of Using Mixed Methods

Part II: Getting Mixed Methods Research Funded

1. 4Writing a Scientifically Sound and Compelling Grant Proposal for a Mixed Methods Study
2. 5Examples of Funded Grant Applications Using Mixed Methods
3. 6Assessing Quality in Mixed Methods Studies

Part III: Designing and Implementing a Mixed Methods Study

1. 7Sampling and Data Collection in Mixed Methods Studies
2. 8Data Analysis and Integration in Mixed Methods Studies
3. 9Managing Mixed Methods Teams
4. 10Implementation Issues in Mixed Methods Research

Part IV: Disseminating Findings

1. 11Publishing Mixed Methods Studies in the Health Sciences

1. 1Introduction to Health Measurement Scales
2. 2Basic Concepts
3. 3Devising the Items
4. 4Scaling Responses
5. 5Selecting the Items
6. 6Biases in Responding
7. 7From Items to Scales
8. 8Reliability
9. 9Generalizability Theory
10. 10Validity
11. 11Measuring Change
12. 12Item Response Theory
13. 13Methods of Administration
14. 14Ethical Considerations
15. 15Reporting Test Results

1. 1Introduction
2. 2Concepts, Theories and Models, and Types of Measurements
3. 3Development of a Measurement Instrument
4. 4Field-Testing: Item Reduction and Data Structure
5. 5Reliability
6. 6Validity
7. 7Responsiveness
8. 8Interpretability
9. 9Systematic Reviews of Measurement Properties

1. 1Statistics in Medical Research
2. 2Types of Data
3. 3Describing Data
4. 4Theoretical Distributions
5. 5Designing Research
6. 6Using a Computer
7. 7Preparing to Analyse Data
8. 8Principles of Statistical Analysis
9. 9Comparing Groups: Continuous Data
10. 10Comparing Groups: Categorical Data
11. 11Relation Between Two Continuous Variables
12. 12Relation Between Several Variables
13. 13Analysis of Survival Times
14. 14Some Common Problems in Medical Research
15. 15Clinical Trials
16. 16The Medical Literature

1. 1Using This Book
2. 2Defining the Data
3. 3Displaying the Data
4. 4Means, Standard Deviations and Standard Errors
5. 5The Normal Distribution
6. 6Confidence Interval for a Mean
7. 7Comparison of Two Means: Confidence Intervals, Hypothesis Tests and P-values
8. 8Using P-values and Confidence Intervals to Interpret the Results of Statistical Analyses
9. 9Comparison of Means from Several Groups: Analysis of Variance
10. 10Linear Regression and Correlation
11. 11Multiple Regression
12. 12Goodness of Fit and Regression Diagnostics
13. 13Transformations
14. 14Probability, Risk and Odds (of Disease)
15. 15Proportions and the Binomial Distribution
16. 16Comparing Two Proportions
17. 17Chi-Squared Tests for 2×2 and Larger Contingency Tables
18. 18Controlling for Confounding: Stratification
19. 19Logistic Regression: Comparing Two or More Exposure Groups
20. 20Logistic Regression: Controlling for Confounding and Other Extensions
21. 21Matched Studies
22. 22Longitudinal Studies, Rates and the Poisson Distribution
23. 23Comparing Rates
24. 24Poisson Regression
25. 25Standardization
26. 26Survival Analysis: Displaying and Comparing Survival Patterns
27. 27Regression Analysis of Survival Data
28. 28Likelihood
29. 29Regression Modelling
30. 30Relaxing Model Assumptions
31. 31Analysis of Clustered Data
32. 32Systematic Reviews and Meta-Analysis
33. 33Bayesian Statistics
34. 34Linking Analysis to Study Design: Summary of Methods
35. 35Calculation of Required Sample Size
36. 36Measurement Error: Assessment and Implications
37. 37Measures of Association and Impact
38. 38Strategies for Analysis

1. 1General Overview
2. 2Descriptive Statistics
3. 3Probability
4. 4Discrete Probability Distributions
5. 5Continuous Probability Distributions
6. 6Estimation
7. 7Hypothesis Testing: One-Sample Inference
8. 8Hypothesis Testing: Two-Sample Inference
9. 9Nonparametric Methods
10. 10Hypothesis Testing: Categorical Data
11. 11Regression and Correlation Methods
12. 12Multisample Inference
13. 13Design and Analysis Techniques for Epidemiologic Studies
14. 14Hypothesis Testing: Person-Time Data

1. 1Introduction
2. 2Exploratory and Descriptive Methods
3. 3Basic Statistical Methods
4. 4Linear Regression
5. 5Logistic Regression
6. 6Survival Analysis
7. 7Repeated Measures and Longitudinal Data Analysis
8. 8Generalized Linear Models
9. 9Strengthening Causal Inference
10. 10Predictor Selection
11. 11Missing Data
12. 12Complex Surveys
13. 13Summary

1. 1Introduction
2. 2General Aspects of Fitting Regression Models
3. 3Missing Data
4. 4Multivariable Modeling Strategies
5. 5Describing, Resampling, Validating, and Simplifying the Model
6. 6R Software
7. 7Modeling Longitudinal Responses using Generalized Least Squares
8. 8Case Study in Data Reduction
9. 9Overview of Maximum Likelihood Estimation
10. 10Binary Logistic Regression
11. 11Case Study in Binary Logistic Regression, Model Selection and Approximation: Predicting Cause of Death
12. 12Logistic Model Case Study 2: Survival of Titanic Passengers
13. 13Ordinal Logistic Regression
14. 14Case Study in Ordinal Regression, Data Reduction, and Penalization
15. 15Regression Models for Continuous Y and Case Study in Ordinal Regression
16. 16Transform-Both-Sides Regression
17. 17Introduction to Survival Analysis
18. 18Parametric Survival Models
19. 19Case Study in Parametric Survival Modeling and Model Approximation
20. 20Cox Proportional Hazards Regression Model
21. 21Case Study in Cox Regression

Part I: Prediction Models in Medicine

1. 1Introduction
2. 2Applications of Prediction Models
3. 3Study Design for Prediction Modeling
4. 4Statistical Models for Prediction
5. 5Overfitting and Optimism in Prediction Models
6. 6Choosing Between Alternative Models

Part II: Developing Valid Prediction Models

1. 7Missing Values
2. 8Case Study on Dealing with Missing Values
3. 9Coding of Categorical and Continuous Predictors
4. 10Restrictions on Candidate Predictors
5. 11Selection of Main Effects
6. 12Assumptions in Regression Models: Additivity and Linearity
7. 13Modern Estimation Methods
8. 14Estimation with External Information
9. 15Evaluation of Performance
10. 16Evaluation of Clinical Usefulness
11. 17Validation of Prediction Models
12. 18Presentation Formats

Part III: Generalizability of Prediction Models

1. 19Patterns of External Validity
2. 20Updating for a New Setting
3. 21Updating for Multiple Settings

Part IV: Applications

1. 22Case Study on a Prediction of 30-Day Mortality
2. 23Case Study on Survival Analysis: Prediction of Cardiovascular Events
3. 24Overall Lessons and Data Sets

1. 1Introduction to Economic Evaluation
2. 2Making Decisions in Health Care
3. 3Critical Assessment of Economic Evaluation
4. 4Principles of Economic Evaluation
5. 5Measuring and Valuing Effects: Health Gain
6. 6Measuring and Valuing Effects: Consumption Benefits of Health Care
7. 7Cost Analysis
8. 8Using Clinical Studies as Vehicles for Economic Evaluation
9. 9Economic Evaluation Using Decision-Analytic Modelling
10. 10Identifying, Synthesizing, and Analysing Evidence for Economic Evaluation
11. 11Characterizing, Reporting, and Interpreting Uncertainty
12. 12How to Take Matters Further

Section 1: Background

1. 1The Promise and Challenges of Dissemination and Implementation Research
2. 2Terminology for Dissemination and Implementation Research

Section 2: Theory and Conceptual Foundations

1. 3Historical Roots of Dissemination and Implementation Science
2. 4The Conceptual Basis for D&I Research: Lessons From Existing Theories, Models, and Frameworks
3. 5Ethical Issues in Dissemination and Implementation Research

Section 3: Strategies and Methods

1. 6Implementation Strategies
2. 7Fidelity and Its Relationship to Effectiveness, Adaptation, and Implementation
3. 8Adaptation in Dissemination and Implementation Science
4. 9The Role of Organizational Processes in D&I Research
5. 10Participatory Approaches in D&I Science
6. 11The Role of Economic Evaluation in D&I Research
7. 12Missing the Target: Mis-implementation and De-implementation
8. 13Systems Science Methods in D&I Research

Section 4: Design and Measurement

1. 14Design and Analysis in D&I Research
2. 15Measurement Issues in D&I Research
3. 16Paying More Attention to External Validity Through an Equity Lens
4. 17Evaluation Approaches for D&I Research
5. 18Mixed-Methods Evaluation in D&I Science

Section 5: Setting- and Population-Specific D&I

1. 19D&I Research in Community and Public Health Settings
2. 20D&I in Social Service Settings
3. 21Implementation Science in Healthcare
4. 22Health D&I Within Schools
5. 23D&I Research in the Workplace
6. 24Policy D&I Research
7. 25Health Equity in D&I Science
8. 26Implementation Science in the Global Context

Section 6: Dissemination and Scale-Up

1. 27Designing for Dissemination and Sustainability
2. 28Enhancing Dissemination Through Marketing and Distribution Systems
3. 29Scale-up and Sustainment of Effective Interventions
4. 30Training and Capacity Building in D&I Science