000			01349cam a2200217 i 4500
001			21318359
010			_a 2019037043
020			_a9781544310305
082	0	0	_a519.535 _bLUK/M
100	1		_aLuke, Douglas A.
245	1	0	_aMultilevel modeling
250			_a2
260			_aNew Delhi _bSage _c2020
300			_axv, 107p.
490	0		_aQuantitative applications in the social sciences ;143
520			_a"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"--
650		0	_aMultivariate analysis.
650		0	_aStructural equation modeling
650		0	_aMultilevel models (Statistics)
942			_cBK
999			_c62933 _d62933