{"tema_id":"2181","string":"Hierarchical Linear Modeling","created":"2022-05-09 19:03:26","code":null,"notes":[{"@type":"Definition note","@lang":"en-GB","@value":"\"Hierarchical linear modeling (HLM) is a particular regression model that is designed to take into account the hierarchical or nested structure of the data. HLM is also known as multi-level modeling, linear mixed-effects model, or covariance components model.\"\nSource: Goldstein, A. and Leyland, A. (2001). Multilevel Modelling of health statistics. Series: Wiley series in probability and statistics.\u00a0\nCited after: Matsuyama, Y. (2013). Hierarchical Linear Modeling (HLM). Gellman, M.D., Turner, J.R. (eds) Encyclopedia of Behavioral Medicine.\u00a0\nOnline: https:\/\/link.springer.com\/referenceworkentry\/10.1007\/978-1-4419-1005-9_407#:~:text=Definition,Leyland%20%26%20Goldstein%2C%202001).\u00a0"}]}