Willkommen, schön sind Sie da!
Logo Ex Libris

Growth Curve Analysis and Visualization Using R

  • E-Book (pdf)
  • 188 Seiten
(0) Erste Bewertung abgeben
Bewertungen
(0)
(0)
(0)
(0)
(0)
Alle Bewertungen ansehen
Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sci... Weiterlesen
E-Books ganz einfach mit der kostenlosen Ex Libris-Reader-App lesen. Hier erhalten Sie Ihren Download-Link.
CHF 120.90
Download steht sofort bereit
Informationen zu E-Books
E-Books eignen sich auch für mobile Geräte (sehen Sie dazu die Anleitungen).
E-Books von Ex Libris sind mit Adobe DRM kopiergeschützt: Erfahren Sie mehr.
Weitere Informationen finden Sie hier.

Beschreibung

Learn How to Use Growth Curve Analysis with Your Time Course Data An increasingly prominent statistical tool in the behavioral sciences, multilevel regression offers a statistical framework for analyzing longitudinal or time course data. It also provides a way to quantify and analyze individual differences, such as developmental and neuropsychological, in the context of a model of the overall group effects. To harness the practical aspects of this useful tool, behavioral science researchers need a concise, accessible resource that explains how to implement these analysis methods.Growth Curve Analysis and Visualization Using R provides a practical, easy-to-understand guide to carrying out multilevel regression/growth curve analysis (GCA) of time course or longitudinal data in the behavioral sciences, particularly cognitive science, cognitive neuroscience, and psychology. With a minimum of statistical theory and technical jargon, the author focuses on the concrete issue of applying GCA to behavioral science data and individual differences. The book begins with discussing problems encountered when analyzing time course data, how to visualize time course data using the ggplot2 package, and how to format data for GCA and plotting. It then presents a conceptual overview of GCA and the core analysis syntax using the lme4 package and demonstrates how to plot model fits. The book describes how to deal with change over time that is not linear, how to structure random effects, how GCA and regression use categorical predictors, and how to conduct multiple simultaneous comparisons among different levels of a factor. It also compares the advantages and disadvantages of approaches to implementing logistic and quasi-logistic GCA and discusses how to use GCA to analyze individual differences as both fixed and random effects. The final chapter presents the code for all of the key examples along with samples demonstrating how to report GCA results.Throughout the book, R code illustrates how to implement the analyses and generate the graphs. Each chapter ends with exercises to test your understanding. The example datasets, code for solutions to the exercises, and supplemental code and examples are available on the author's website.

Produktinformationen

Titel: Growth Curve Analysis and Visualization Using R
Autor:
EAN: 9781466584334
ISBN: 978-1-4665-8433-4
Digitaler Kopierschutz: Adobe-DRM
Format: E-Book (pdf)
Herausgeber: Crc Press
Genre: Sonstiges Geisteswissenschaften, Kunst, Musik
Anzahl Seiten: 188
Veröffentlichung: 18.04.2014
Jahr: 2016
Untertitel: Englisch