Multilevel modeling for repeated measures: Difference between revisions

Revision as of 11:08, 28 August 2014

Revision as of 10:58, 28 October 2014

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:(2) The dependent variable is assumed to be normally distributed. ''However,'' binary and discrete dependent variables may be examined in MLM using specialized procedures (i.e. employ different [[link function]]s).<ref>{{cite book|last=Snijders|first=Tom A.B.|title=Multilevel analysis : an introduction to basic and advanced multilevel modeling|year=2002|publisher=Sage Publications|___location=London|isbn=978-0761958901|edition=Reprint.|author2=Bosker, Roel J.}}</ref>

One of the assumptions of using MLM for growth curve modeling is that all subjects show the same relationship over time (e.g. linear, quadratic etc.). Another assumption of MLM for growth curve modeling is that the observed changes are related to the passage of time.<ref name=hox>{{cite book|last=Hox|first=Joop|authorlink=Joop Hox|title=Multilevel and SEM Approached to Growth Curve Modeling|year=2005|publisher=Wiley|___location=Chichester|isbn=978-0-470-86080-9|url=http://joophox.net/publist/ebs05.pdf|edition=[Repr.].}}</ref>

==Statistics & Interpretation==

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*{{cite book|last=Howell|first=David C.|title=Statistical methods for psychology|year=2010|publisher=Thomson Wadsworth|___location=Belmont, CA|isbn=978-0-495-59784-1|edition=7th ed.}}

*{{cite book|last=Hox|first=Joop|authorlink=Joop Hox|title=Multilevel and SEM Approached to Growth Curve Modeling|year=2005|publisher=Wiley|___location=Chichester|isbn=978-0-470-86080-9|url=http://joophox.net/publist/ebs05.pdf|edition=[Repr.].}}

*{{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}}