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Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS
Langbeschreibung
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
Qingzhao Yu is Professor in Biostatistics, Louisiana State University Health Sciences Center.
ISBN-13:
9781000549416
Veröffentl:
2022
Seiten:
294
Autor:
Qingzhao Yu
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
0 - No protection
Sprache:
Englisch
67,49 €*
Lieferzeit: Sofort lieferbar
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