The Resource Data analysis using regression and multilevel/hierarchical models, Andrew Gelman, Jennifer Hill

Data analysis using regression and multilevel/hierarchical models, Andrew Gelman, Jennifer Hill

Label
Data analysis using regression and multilevel/hierarchical models
Title
Data analysis using regression and multilevel/hierarchical models
Statement of responsibility
Andrew Gelman, Jennifer Hill
Creator
Contributor
Subject
Language
eng
Summary
"Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout."--Publisher description
Member of
Cataloging source
N$T
Dewey number
519.5/36
Illustrations
illustrations
Index
index present
LC call number
HA31.3
LC item number
.G45 2007eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Analytical methods for social research
Label
Data analysis using regression and multilevel/hierarchical models, Andrew Gelman, Jennifer Hill
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references (pages 575-600) and indexes
http://library.link/vocab/branchCode
  • net
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
mixed
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Why? -- Concepts and methods from basic probability and statistics -- Linear regression: the basics -- Linear regression: before and after fitting the model -- Logistic regression -- Generalized linear models -- Simulation for checking statistical procedures and model fits -- Causal inference using regression on the treatment variable -- Causal inference using more advanced models -- Multilevel structures -- Multilevel linear models: the basics -- Multilevel linear models: varying slopes, non-nested models, and other complexities -- Multilevel logistic regression -- Multilevel generalized linear models -- Multilevel modeling Bugs and R: the basics -- Fitting multilevel linear and generalized linear models in Bugs and R -- Likelihood and Bayesian inference and computation -- Debugging and speeding convergence -- Sample size and power calculations -- Understanding and summarizing the fitted models -- Analysis of variance -- Causal inference using multilevel models -- Model checking and comparison -- Missing-data imputation -- Six quick tips to improve your regression modeling -- Statistical graphics for research and presentation -- Software
Control code
ocn646068240
Dimensions
unknown
Extent
1 online resource (xxii, 625 pages)
File format
unknown
Form of item
online
Isbn
9780511268113
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations
Quality assurance targets
not applicable
http://library.link/vocab/recordID
.b22607778
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)646068240
  • pebco0511268114

Library Locations

    • Deakin University Library - Geelong Waurn Ponds CampusBorrow it
      75 Pigdons Road, Waurn Ponds, Victoria, 3216, AU
      -38.195656 144.304955
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