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Multilevel Model Foundations - Monopoly® Data and Stata
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Multilevel Model Foundations - Monopoly® Data and Stata
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This book introduces the foundations of multilevel models, using
Monopoly® rent data from the classic board game, and the
statistical program Stata®. Widespread experience with the game
means many readers have a head start on understanding these models.
The small data set, 132 rent values for 22 properties clustered by
the four sides of the playing board, combines with extensive
graphical displays of data and results so all readers can see core
multilevel ideas in action at a granular level. Two chapters on
standard statistical models, oneway analysis of variance and
multiple regression, help readers see how multilevel models rely on
but also extend these monolevel ideas. Chapters present three basic
multilevel models for cross-sectional analyses – analysis of
variance, analysis of covariance, and random coefficients
regression – and one basic developmental model for longitudinal
analyses. Troubleshooting guidance, combined with close examination
of data patterns, and careful inspection of model parameters, all
help readers better grasp what model results mean, when model
results should or should not be trusted, and how model results link
back to core theoretical questions. Consequently, readers will
develop a sense of best practices for building and diagnosing their
own multilevel models. Those who complete the volume can readily
apply what they have learned to more complex datasets and models,
and adapt available online Stata do files to those projects. Any
social scientist working with data clustered in time, in space, or
in both, and seeking to learn more about how to use, interpret, or
teach these models, will find the book useful.
General
Imprint: |
Taylor & Francis
|
Country of origin: |
United Kingdom |
Release date: |
December 2023 |
First published: |
2024 |
Authors: |
Ralph B. Taylor
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Dimensions: |
216 x 138mm (L x W) |
Pages: |
200 |
ISBN-13: |
978-1-03-243197-0 |
Categories: |
Books
Promotions
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LSN: |
1-03-243197-0 |
Barcode: |
9781032431970 |
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