title: Multilevel modeling and model averaging.
abstract: Multilevel modeling, also known as hierarchical regression, generalizes ordinary regression modeling to allow explicit and flexible compromises between simple and complex models. This article provides an elementary introduction to multilevel modeling as a model-averaging technique. Model averaging provides an alternative to model selection, and it emphasizes the role of prior information in finding good models.
authors.affiliation: Department of Epidemiology, UCLA School of Public Health, Los Angeles, California, USA.
authors.forename: S
authors.initials: S
authors.lastname: Greenland
mesh_terms: D000022:Abortion, Spontaneous / Q000453:epidemiology / Q000209:etiology; D000328:Adult; D001499:Bayes Theorem; D015982:Bias; D015986:Confounding Factors, Epidemiologic; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D015233:Models, Statistical; D011247:Pregnancy; D012044:Regression Analysis; D015203:Reproducibility of Results; D012307:Risk Factors; D014876:Water Pollution / Q000009:adverse effects