Multilevel modeling / Douglas A. Luke, Washington University in St. Louis.

By:

Luke, Douglas A [author.]

Material type: Text

TextSeries: Quantitative applications in the social sciences ; 143Publisher: Los Angeles : SAGE Publishing, [2020]Edition: Second editionDescription: xv, 107 pages ; 22 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9781544310305

Subject(s):

DDC classification:

519.5/35 23

LOC classification:

QA278 .L85 2020

Summary: "Since the 1st edition of this monograph was published in 2004, there have been numerous developments in the statistical and computational methods used in multilevel and longitudinal modeling. Mixed-effects modeling has been solidified as a primary means for accurately and efficiently estimating a wide-variety of multilevel and longitudinal models. More complex models that include cross-level interactions, cross-classified random effects, alternative covariances structures, and the like appear much more frequently in the health and social sciences research literature. Sophisticated mixedeffects modeling procedures are now incorporated in most comprehensive statistical software packages (including R, Stata, and SAS), and thus there is less need for specialized multilevel software"-- Provided by publisher.

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Book	Indian Institute of Management Visakhapatnam - Andhra University	519.5 LUK (Browse shelf(Opens below))	Available		001443

Includes bibliographical references (pages 100-104) and index.

"Since the 1st edition of this monograph was published in 2004, there have been numerous developments in the statistical and computational methods used in multilevel and longitudinal modeling. Mixed-effects modeling has been solidified as a primary means for accurately and efficiently estimating a wide-variety of multilevel and longitudinal models. More complex models that include cross-level interactions, cross-classified random effects, alternative covariances structures, and the like appear much more frequently in the health and social sciences research literature. Sophisticated mixedeffects modeling procedures are now incorporated in most comprehensive statistical software packages (including R, Stata, and SAS), and thus there is less need for specialized multilevel software"-- Provided by publisher.

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