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This book introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis. Inhaltsverzeichnis 1 Introduction 2 A Review of Third-Variable Effect Inferences 3 Advanced Statistical Modeling and Machine Learning Methods Used in the Book 4 The General Third-Variable Effect Analysis Method 5 The Implementation of General Third-Variable Effect Analysis Method 6 Assumptions for the General Third-Variable Analysis 7 Multiple Exposures and Multivariate Responses 8 Regularized Third-Variable Effect Analysis for High-Dimensional Dataset 9 Interaction/Moderation Analysis with Third-Variable Effects 10 Third-Variable Effect Analysis with Multilevel Additive Models 11 Bayesian Third-Variable Effect Analysis 12 Other Issues
Buchkauf
Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS, Bin Li, Qingzhao Yu
- Sprache
- Erscheinungsdatum
- 2024
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- Titel
- Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS
- Sprache
- Englisch
- Autor*innen
- Bin Li, Qingzhao Yu
- Verlag
- Taylor & Francis Ltd
- Erscheinungsdatum
- 2024
- Einband
- Paperback
- Seitenzahl
- 294
- ISBN13
- 9781032220086
- Kategorie
- Mathematik
- Beschreibung
- This book introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis. Inhaltsverzeichnis 1 Introduction 2 A Review of Third-Variable Effect Inferences 3 Advanced Statistical Modeling and Machine Learning Methods Used in the Book 4 The General Third-Variable Effect Analysis Method 5 The Implementation of General Third-Variable Effect Analysis Method 6 Assumptions for the General Third-Variable Analysis 7 Multiple Exposures and Multivariate Responses 8 Regularized Third-Variable Effect Analysis for High-Dimensional Dataset 9 Interaction/Moderation Analysis with Third-Variable Effects 10 Third-Variable Effect Analysis with Multilevel Additive Models 11 Bayesian Third-Variable Effect Analysis 12 Other Issues