R. Karl Hanson
Prediction Statistics for Psychological Assessment
R. Karl Hanson
Prediction Statistics for Psychological Assessment
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A comprehensive survey of prediction statistics that illustrates the utility of prediction tools in applied psychological practice.
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A comprehensive survey of prediction statistics that illustrates the utility of prediction tools in applied psychological practice.
Produktdetails
- Produktdetails
- Verlag: American Psychological Association (APA)
- Seitenzahl: 448
- Erscheinungstermin: 14. Dezember 2021
- Englisch
- Abmessung: 253mm x 179mm x 24mm
- Gewicht: 762g
- ISBN-13: 9781433836411
- ISBN-10: 1433836416
- Artikelnr.: 61930315
- Verlag: American Psychological Association (APA)
- Seitenzahl: 448
- Erscheinungstermin: 14. Dezember 2021
- Englisch
- Abmessung: 253mm x 179mm x 24mm
- Gewicht: 762g
- ISBN-13: 9781433836411
- ISBN-10: 1433836416
- Artikelnr.: 61930315
R. Karl Hanson
Preface
Part I: Background and Overview
Chapter 1: Introduction to Prediction Statistics in Psychology
Chapter 2: The Nature of Probability
Chapter 3: Overview of the Statistics Chapters
Part II: Statistics for Describing Likelihoods
Chapter 4: Proportions
Chapter 5: Discrete-Time Survival Analysis
Chapter 6: Kaplan-Meier Survival Analysis
Part III: Discrimination and Relative Risk
Chapter 7: Dichotomous Predictors
Chapter 8: Area Under the Curve
Chapter 9: Cohen's d
Chapter 10: Cox Regression
Chapter 11: Logistic Regression
Part IV: Calibration
Chapter 12: Chi-Square Goodness-of-Fit
Chapter 13: The E/O Index
Chapter 14: Meta-Analysis
Chapter 15: Calibration Plots
Part V: Percentile Ranks
Chapter 16: Percentiles
Part VI: Practice Considerations
Chapter 17: Estimating the Quality of Prediction Tools
Chapter 18: Standardizing Risk Communication
Chapter 19: Going Even Further
Appendix: Useful Algebra and Notation
Glossary
References
Index
About the Authors
Part I: Background and Overview
Chapter 1: Introduction to Prediction Statistics in Psychology
Chapter 2: The Nature of Probability
Chapter 3: Overview of the Statistics Chapters
Part II: Statistics for Describing Likelihoods
Chapter 4: Proportions
Chapter 5: Discrete-Time Survival Analysis
Chapter 6: Kaplan-Meier Survival Analysis
Part III: Discrimination and Relative Risk
Chapter 7: Dichotomous Predictors
Chapter 8: Area Under the Curve
Chapter 9: Cohen's d
Chapter 10: Cox Regression
Chapter 11: Logistic Regression
Part IV: Calibration
Chapter 12: Chi-Square Goodness-of-Fit
Chapter 13: The E/O Index
Chapter 14: Meta-Analysis
Chapter 15: Calibration Plots
Part V: Percentile Ranks
Chapter 16: Percentiles
Part VI: Practice Considerations
Chapter 17: Estimating the Quality of Prediction Tools
Chapter 18: Standardizing Risk Communication
Chapter 19: Going Even Further
Appendix: Useful Algebra and Notation
Glossary
References
Index
About the Authors
Preface
Part I: Background and Overview
Chapter 1: Introduction to Prediction Statistics in Psychology
Chapter 2: The Nature of Probability
Chapter 3: Overview of the Statistics Chapters
Part II: Statistics for Describing Likelihoods
Chapter 4: Proportions
Chapter 5: Discrete-Time Survival Analysis
Chapter 6: Kaplan-Meier Survival Analysis
Part III: Discrimination and Relative Risk
Chapter 7: Dichotomous Predictors
Chapter 8: Area Under the Curve
Chapter 9: Cohen's d
Chapter 10: Cox Regression
Chapter 11: Logistic Regression
Part IV: Calibration
Chapter 12: Chi-Square Goodness-of-Fit
Chapter 13: The E/O Index
Chapter 14: Meta-Analysis
Chapter 15: Calibration Plots
Part V: Percentile Ranks
Chapter 16: Percentiles
Part VI: Practice Considerations
Chapter 17: Estimating the Quality of Prediction Tools
Chapter 18: Standardizing Risk Communication
Chapter 19: Going Even Further
Appendix: Useful Algebra and Notation
Glossary
References
Index
About the Authors
Part I: Background and Overview
Chapter 1: Introduction to Prediction Statistics in Psychology
Chapter 2: The Nature of Probability
Chapter 3: Overview of the Statistics Chapters
Part II: Statistics for Describing Likelihoods
Chapter 4: Proportions
Chapter 5: Discrete-Time Survival Analysis
Chapter 6: Kaplan-Meier Survival Analysis
Part III: Discrimination and Relative Risk
Chapter 7: Dichotomous Predictors
Chapter 8: Area Under the Curve
Chapter 9: Cohen's d
Chapter 10: Cox Regression
Chapter 11: Logistic Regression
Part IV: Calibration
Chapter 12: Chi-Square Goodness-of-Fit
Chapter 13: The E/O Index
Chapter 14: Meta-Analysis
Chapter 15: Calibration Plots
Part V: Percentile Ranks
Chapter 16: Percentiles
Part VI: Practice Considerations
Chapter 17: Estimating the Quality of Prediction Tools
Chapter 18: Standardizing Risk Communication
Chapter 19: Going Even Further
Appendix: Useful Algebra and Notation
Glossary
References
Index
About the Authors