Multilevel modeling, Series: Quantitative Applications in the Social Sciences by Douglas a. Luke

By:

Douglas a. Luke [Author]

Publication details: Sage New Delhi 2004Description: vi, 79 pages; Illustrations; 21 cmISBN:

9780761928799

DDC classification:

519.535 LUK

Contents:

The Need for Multilevel Modeling Theoretical reasons for multilevel models Statistical reasons for multilevel models Scope of Book Basic Multilevel Modeling The basic two-level multilevel model How to build and evaluate a multilevel model Extending the Basic Multilevel Model Using generalized multilevel modeling Three-level models Longitudinal data as hierarchical: Time nested within person Appendices Datasets and other support materials Software Other Resources

Abstract: Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Book	Indian Institute of Management Visakhapatnam General Stacks	Non-fiction	519.535 LUK (Browse shelf(Opens below))	Checked out	04/23/2023	001259

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Previous	519.502465 STI Statistics for Business: Decision Making and Analysis	519.535 ALD Cluster Analysis, Series: Quantitative Applications in the Social Sciences	519.535 LIU Applied Ordinal Logistic Regressi Using Stata: From Single-Level to Multilevel Modeling	519.535 LUK Multilevel modeling, Series: Quantitative Applications in the Social Sciences	519.5350285 SCH Using R With Multivariate Statistics	519.5350285536 BLU Introduction to Structural Equation Modeling Using IBM SPSS Statistics and Amos /	519.536 LEW Applied regression an introduction	Next

The Need for Multilevel Modeling
Theoretical reasons for multilevel models

Statistical reasons for multilevel models

Scope of Book

Basic Multilevel Modeling
The basic two-level multilevel model

How to build and evaluate a multilevel model

Extending the Basic Multilevel Model
Using generalized multilevel modeling

Three-level models

Longitudinal data as hierarchical: Time nested within person

Appendices
Datasets and other support materials Software Other Resources

Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models.

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