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Beschreibung
This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time.
This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time.
Über den Autor

Ralitza Gueorguieva is a Senior Research Scientist at the Department of Biostatistics, Yale School of Public Health. She has more than 20 years experience in statistical methodology development and collaborations with psychiatrists and other researchers, and is the author of over 130 peer-reviewed publications.

Inhaltsverzeichnis

Introduction

Traditional Methods for Analysis of Longitudinal and Clustered Data

Linear Mixed Models for Longitudinal and Clustered Data

Linear Models for Non-normal Outcomes

Nonparametric Methods for the Analysis of Repeatedly Measured Data

Post-hoc Analysis and Adjustments for Multiple Comparisons

Handling of Missing Data and Dropout in Longitudinal Studies

Controlling for Covariates in Studies with Repeated Measures

Assessment of Moderator and Mediator Effects

Mixture Models for Trajectory Analyses

Study Design and Sample Size Calculations

Summary and Further Readings

Details
Erscheinungsjahr: 2020
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Importe, Mathematik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780367657529
ISBN-10: 036765752X
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Gueorguieva, Ralitza
Hersteller: Chapman and Hall/CRC
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 254 x 178 x 20 mm
Von/Mit: Ralitza Gueorguieva
Erscheinungsdatum: 30.09.2020
Gewicht: 0,699 kg
Artikel-ID: 133317300

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