Multilevel modeling for repeated measures: Difference between revisions

Revision as of 17:33, 14 December 2015

Revision as of 20:15, 7 April 2016

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::'''5. MLM is relatively easily extended to discrete data.''' <ref>{{cite book | last = Molenberghs | first = Geert | title = Models for discrete longitudinal data | publisher = Springer Science+Business Media, Inc | ___location = New York | year = 2005 | isbn = 978-0387251448 }}</ref>

::''Note:'' Although [[missing data]] is permitted in MLM, it is assumed to be missing at random. Thus, systematically missing data can present problems.<ref name=quene /><ref>{{cite journal|last=Overall|first=John E.|author2=Tonidandel, Scott|title=Analysis of Data from a Controlled Repeated Measurements Design with Baseline-Dependent Dropouts|journal=Methodology: European Journal of Research Methods for the Behavioral and Social Sciences|year=2007|volume=3|issue=2|pages=58–66|doi=10.1027/1614-2241.3.2.58}}</ref><ref>{{cite journal|lastlast1=Overall|firstfirst1=John|coauthorslast2=Ahn, |first2=Chul, |last3=Shivakumar, |first3=C., |last4=Kalburgi, |first4=Yallapa|title=PROBLEMATICProblematic FORMULATIONSformulations OFof SAS PROC.MIXED MODELSmodels FORfor REPEATEDrepeated MEASUREMENTSmeasurements|journal=Journal of Biopharmaceutical Statistics|year=20071999|volume=9|issue=1|pages=189–216|doi=10.1081/BIP-100101008}}</ref>

===Multilevel Modeling versus Structural Equation Modeling (SEM; Latent Growth Model)===