Multilevel Analysis : Techniques and applications

By:

Hox, Joop J [author.]

Contributor(s):

Material type:

TextLanguage: English Series: Quantitative Methodology SeriesPublication details: New York : Routledge/Taylor & Francis, 2018.Edition: 3rd edDescription: xv, 347p. : ill. ; 23 cmISBN:

9781032938035

Subject(s):

Other classification:

B284 Q0;Q8

Summary: The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software

Item type:

Textual

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Holdings
Cover image	Item type	Current library	Home library	Collection	Shelving location	Call number	Materials specified	Vol info	URL	Copy number	Status	Notes	Date due	Barcode	Item holds	Item hold queue priority	Course reserves
	Textual	Central Science Library	Central Science Library			B284 Q0;Q8 (Browse shelf(Opens below))					Available			SL1655992

Includes appendix, references and index.

The book also includes advanced extensions, making it useful as both an introduction for students and as a reference for researchers. Basic models and examples are discussed in nontechnical terms with an emphasis on understanding the methodological and statistical issues involved in using these models. The estimation and interpretation of multilevel models is demonstrated using realistic examples from various disciplines including psychology, education, public health, and sociology. Readers are introduced to a general framework on multilevel modeling which covers both observed and latent variables in the same model, while most other books focus on observed variables. In addition, Bayesian estimation is introduced and applied using accessible software

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