000			03186cam a2200421 a 4500
001			17211607
005			20131008130022.0
007			Paper bound
008			120315s2012 nyua b 001 0 eng
010			_a 2012004179
020			_a9781848729568
040			_aDLC _cDLC _ddlc
042			_apcc
050	0	0	_aBF39 _b.H353 2012
082	0	0	_a300.285555 _222 _bHE-M
084			_aPSY032000 _aEDU027000 _aSOC027000 _2bisacsh
100	1		_aHeck, Ronald H.
100	1		_aThomas, Scott.
100	1		_aTabata, Lynn Naomi.
245	1	0	_aMultilevel modeling of categorical outcomes using IBM SPSS
260			_aLondon _bRoutledge _c2012
300			_axvi,439p. _bill. ; _c29 cm.
490	0		_aQuantitative methodology series
504			_aIncludes bibliographical references (p. 405-408) and index.
520			_a"Preface Multilevel modeling has become a mainstream data analysis tool over the past decade, now figuring prominently in a range of social and behavioral science disciplines. Where it originally required specialized software, mainstream statistics packages such as IBM SPSS, SAS, and Stata all have included routines for multilevel modeling in their programs. Although some devotees of these statistical packages have been making good use of the relatively new multilevel modeling functionality, progress has been slower in carefully documenting these routines to facilitate meaningful access to the average user. Two years ago we developed Multilevel and Longitudinal Modeling with IBM SPSS to demonstrate how to use these techniques in IBM SPSS Version 18. Our focus was on developing a set of concepts and programming skills within the IBM SPSS environment that could be used to develop, specify, and test a variety of multilevel models with continuous outcomes, since IBM SPSS is a standard analytic tool used in many graduate programs and organizations globally. Our intent was to help readers gain facility in using the IBM SPSS linear-mixed models routine for continuous outcomes. We offered multiple examples of several different types of multilevel models, focusing on how to set up each model and how to interpret the output. At the time, mixed modeling for categorical outcomes was not available in the IBM SPSS software program. Over the past year or so, however, the generalized linear mixed model (GLMM) has been added to the mixed modeling analytic routine in IBM SPSS starting with Version 19. This addition prompted us to create this companion workbook that would focus on introducing readers to the multilevel approach to modeling with categorical outcomes"--
630	0	0	_aSPSS (Computer file)
630	0	0	_aSPSS for Windows.
650		0	_aPsychometrics.
650		0	_aPsychometrics _xComputer programs.
650		0	_aSocial sciences _xComputer programs.
650		7	_aPsychology / Statistics. _2bisacsh
650		7	_aEducation / Statistics. _2bisacsh
650		7	_aSocial Science / Statistics. _2bisacsh
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK
999			_c28873 _d28873