Multilevel modeling

By: Luke, Douglas AMaterial type: TextTextSeries: Quantitative applications in the social sciences ;143Publication details: New Delhi Sage 2020Edition: 2Description: xv, 107pISBN: 9781544310305Subject(s): Multivariate analysis | Structural equation modeling | Multilevel models (Statistics)DDC classification: 519.535 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"--
Tags from this library: No tags from this library for this title. Log in to add tags.
    Average rating: 0.0 (0 votes)
Item type Current library Call number Status Date due Barcode
BK BK
Stack
519.535 LUK/M (Browse shelf (Opens below)) Available 54744

"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"--

There are no comments on this title.

to post a comment.

Powered by Koha