Book contents
- A Clinician’s Guide to Statistics in Mental Health
- A Clinician’s Guide to Statistics in Mental Health
- Copyright page
- Dedication
- Dedication
- Contents
- Preface
- Acknowledgments
- Chapter 1 Why Data Never Speak for Themselves
- Chapter 2 Why You Cannot Believe Your Eyes
- Chapter 3 Levels of Evidence
- Chapter 4 Bias
- Chapter 5 Randomization
- Chapter 6 Clinical Trials: Improving on Clinical Experience
- Chapter 7 P-Values: Uses and Misuses
- Chapter 8 Forget P-Values: The Importance of Effect Sizes
- Chapter 9 Understanding Placebo Effects
- Chapter 10 Understanding Confidence Intervals
- Chapter 11 Observational Studies
- Chapter 12 The Alchemy of Meta-Analysis
- Chapter 13 Bayesian Statistics: Why Your Opinion Counts
- Chapter 14 Causation
- Chapter 15 A Philosophy of Statistics
- Chapter 16 Evidence-Based Medicine: Defense and Criticism
- Chapter 17 Social and Economic Factors: Peer Review, Funding, and the Conventional Wisdom
- Chapter 18 The New Canon of Psychopharmacology (STAR*D, STEP-BD, CATIE): How Clinical Trials Are Misinterpreted
- Chapter 19 How to Analyze a Study
- Chapter 20 False Positive Maintenance Clinical Trials in Psychiatry
- Appendix Understanding Regression
- References
- Index
Chapter 4 - Bias
Published online by Cambridge University Press: 20 January 2023
- A Clinician’s Guide to Statistics in Mental Health
- A Clinician’s Guide to Statistics in Mental Health
- Copyright page
- Dedication
- Dedication
- Contents
- Preface
- Acknowledgments
- Chapter 1 Why Data Never Speak for Themselves
- Chapter 2 Why You Cannot Believe Your Eyes
- Chapter 3 Levels of Evidence
- Chapter 4 Bias
- Chapter 5 Randomization
- Chapter 6 Clinical Trials: Improving on Clinical Experience
- Chapter 7 P-Values: Uses and Misuses
- Chapter 8 Forget P-Values: The Importance of Effect Sizes
- Chapter 9 Understanding Placebo Effects
- Chapter 10 Understanding Confidence Intervals
- Chapter 11 Observational Studies
- Chapter 12 The Alchemy of Meta-Analysis
- Chapter 13 Bayesian Statistics: Why Your Opinion Counts
- Chapter 14 Causation
- Chapter 15 A Philosophy of Statistics
- Chapter 16 Evidence-Based Medicine: Defense and Criticism
- Chapter 17 Social and Economic Factors: Peer Review, Funding, and the Conventional Wisdom
- Chapter 18 The New Canon of Psychopharmacology (STAR*D, STEP-BD, CATIE): How Clinical Trials Are Misinterpreted
- Chapter 19 How to Analyze a Study
- Chapter 20 False Positive Maintenance Clinical Trials in Psychiatry
- Appendix Understanding Regression
- References
- Index
Summary
Bias means systematic error. Its most common form is confounding bias, where various factors in the context of treatment influence the results, without the awareness of clinician or patient. Incorrect claims are made when these confounding factors are ignored. Randomization is the best solution to confounding bias. Clinical examples are provided for antidepressant discontinuation in bipolar depression and for the relationship between substance abuse and antidepressant-related mania. Other forms of bias are discussed, such as measurement bias.
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- A Clinician's Guide to Statistics in Mental Health , pp. 14 - 20Publisher: Cambridge University PressPrint publication year: 2023