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Multilevel Modeling Methods with Introductory and Advanced Applications

List Price: $74.00
SKU:
9781648028717
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  • Product Details

    Author:
    Ann A. O'Connell,, D. Betsy McCoach, Bethany A. Bell
    Format:
    Paperback
    Pages:
    644
    Publisher:
    Emerald Publishing Limited (March 17, 2022)
    Imprint:
    Information Age Publishing
    Language:
    English
    Audience:
    Professional and scholarly
    ISBN-13:
    9781648028717
    ISBN-10:
    1648028713
    Weight:
    31.36oz
    Dimensions:
    6.14" x 9.21" x 1.3"
    File:
    TWO RIVERS-PERSEUS-Metadata_Only_Perseus_Distribution_Customer_Group_Metadata_20251121163228-20251122.xml
    Folder:
    TWO RIVERS
    List Price:
    $74.00
    Country of Origin:
    United Kingdom
    Pub Discount:
    35
    Series:
    Quantitative Methods in Education and the Behavioral Sciences: Issues,
    Case Pack:
    1
    As low as:
    $70.30
    Publisher Identifier:
    P-PER
    Discount Code:
    H
  • Overview

    Multilevel Modeling Methods with Introductory and Advanced Applications provides a cogent and comprehensive introduction to the area of multilevel modeling for methodological and applied researchers as well as advanced graduate students. The book is designed to be able to serve as a textbook for a one or two semester course in multilevel modeling. The topics of the seventeen chapters range from basic to advanced, yet each chapter is designed to be able to stand alone as an instructional unit on its respective topic, with an emphasis on application and interpretation.

    In addition to covering foundational topics on the use of multilevel models for organizational and longitudinal research, the book includes chapters on more advanced extensions and applications, such as cross-classified random effects models, non-linear growth models, mixed effects location scale models, logistic, ordinal, and Poisson models, and multilevel mediation. In addition, the volume includes chapters addressing some of the most important design and analytic issues including missing data, power analyses, causal inference, model fit, and measurement issues. Finally, the volume includes chapters addressing special topics such as using large-scale complex sample datasets, and reporting the results of multilevel designs.