title: Hierarchical Linear Modeling for Analysis of Ecological Momentary Assessment Data in Physical Medicine and Rehabilitation Research.
abstract: Ecological momentary assessment (EMA) methods collect real-time data in real-world environments, which allow physical medicine and rehabilitation researchers to examine objective outcome data and reduces bias from retrospective recall. The statistical analysis of EMA data is directly related to the research question and the temporal design of the study. Hierarchical linear modeling, which accounts for multiple observations from the same participant, is a particularly useful approach to analyzing EMA data. The objective of this paper was to introduce the process of conducting hierarchical linear modeling analyses with EMA data. This is accomplished using exemplars from recent physical medicine and rehabilitation literature.
authors.affiliation: From the Department of Occupational Therapy, School of Health and Rehabilitation Sciences, University of Pittsburgh (LT); Department of Rehabilitation Science and Technology, School of Health and Rehabilitation Sciences, University of Pittsburgh (KBB, KMG); Department of Psychiatry, University of Pittsburgh (ABM); Department of Psychology in Education, School of Education, University of Pittsburgh (FY); and Department of Psychology, University of Pittsburgh (SS), Pennsylvania.
authors.forename: Lauren
authors.initials: L
authors.lastname: Terhorst
authors.forename: Kelly Battle
authors.initials: KB
authors.lastname: Beck
authors.forename: Ashlee B
authors.initials: AB
authors.lastname: McKeon
authors.forename: Kristin M
authors.initials: KM
authors.lastname: Graham
authors.forename: Feifei
authors.initials: F
authors.lastname: Ye
authors.forename: Saul
authors.initials: S
authors.lastname: Shiffman
mesh_terms: D035843:Biomedical Research / Q000379:methods*; D003625:Data Collection / Q000379:methods*; D000072860:Ecological Momentary Assessment; D006801:Humans; D016014:Linear Models; D010810:Physical and Rehabilitation Medicine; D012107:Research Design; D012189:Retrospective Studies