Includes bibliographical references (pages 100-104) and index.
Contents:
The need for multilevel modeling -- Planning a multilevel model -- Building a multilevel model -- Assessing a multilevel model -- Extending the basic model -- Longitudinal models -- Guidance.
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.
Series:
Quantitative applications in the social sciences ; 143
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.