title: Three-level multilevel growth models for nested change data: a guide for group treatment researchers.
abstract: Researchers have known for years about the negative impact on Type I error rates caused by dependencies in hierarchically nested and longitudinal data. Despite this, group treatment researchers do not consistently use methods such as multilevel models (MLMs) to assess dependence and appropriately analyse their nested data. The goals of this study are to review some of the study design issues with regard to hierarchically nested and longitudinal data, discuss MLMs for assessing and handling dependence in data, and present a guide for developing a three-level growth MLM that is appropriate for group treatment data, design, and research questions. The authors present an example from group treatment research to illustrate these issues and methods.
authors.affiliation: Department of Psychology, The Ottawa Hospital-General, Ottawa, Ontario K1H 8L6, Ontario. gtasca@ottawahospital.on.ca
authors.forename: Giorgio A
authors.initials: GA
authors.lastname: Tasca
authors.forename: Vanessa
authors.initials: V
authors.lastname: Illing
authors.forename: Anthony S
authors.initials: AS
authors.lastname: Joyce
authors.forename: John S
authors.initials: JS
authors.lastname: Ogrodniczuk
mesh_terms: D006801:Humans; D001523:Mental Disorders / Q000628:therapy*; D008960:Models, Psychological; D011613:Psychotherapy / Q000379:methods*