An introduction to hierarchical linear modeling
This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis. The first section of the tutorial defines HLM, clarifies its purpo...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Université d'Ottawa
2012-02-01
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Series: | Tutorials in Quantitative Methods for Psychology |
Subjects: | |
Online Access: | http://www.tqmp.org/Content/vol08-1/p052/p052.pdf |
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author | Heather Woltman Andrea Feldstain J. Christine MacKay Meredith Rocchi |
author_facet | Heather Woltman Andrea Feldstain J. Christine MacKay Meredith Rocchi |
author_sort | Heather Woltman |
collection | DOAJ |
description | This tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis. The first section of the tutorial defines HLM, clarifies its purpose, and states its advantages. The second section explains the mathematical theory, equations, and conditions underlying HLM. HLM hypothesis testing is performed in the third section. Finally, the fourth section provides a practical example of running HLM, with which readers can follow along. Throughout this tutorial, emphasis is placed on providing a straightforward overview of the basic principles of HLM. |
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format | Article |
id | doaj.art-81637f881ae74650a6b9f8299b32c690 |
institution | Directory Open Access Journal |
issn | 1913-4126 |
language | English |
last_indexed | 2024-12-10T20:07:42Z |
publishDate | 2012-02-01 |
publisher | Université d'Ottawa |
record_format | Article |
series | Tutorials in Quantitative Methods for Psychology |
spelling | doaj.art-81637f881ae74650a6b9f8299b32c6902022-12-22T01:35:21ZengUniversité d'OttawaTutorials in Quantitative Methods for Psychology1913-41262012-02-01815269An introduction to hierarchical linear modelingHeather WoltmanAndrea FeldstainJ. Christine MacKayMeredith RocchiThis tutorial aims to introduce Hierarchical Linear Modeling (HLM). A simple explanation of HLM is provided that describes when to use this statistical technique and identifies key factors to consider before conducting this analysis. The first section of the tutorial defines HLM, clarifies its purpose, and states its advantages. The second section explains the mathematical theory, equations, and conditions underlying HLM. HLM hypothesis testing is performed in the third section. Finally, the fourth section provides a practical example of running HLM, with which readers can follow along. Throughout this tutorial, emphasis is placed on providing a straightforward overview of the basic principles of HLM.http://www.tqmp.org/Content/vol08-1/p052/p052.pdfHierarchical Linear ModelsNested DataHypothesis TestingParameter Estimation |
spellingShingle | Heather Woltman Andrea Feldstain J. Christine MacKay Meredith Rocchi An introduction to hierarchical linear modeling Tutorials in Quantitative Methods for Psychology Hierarchical Linear Models Nested Data Hypothesis Testing Parameter Estimation |
title | An introduction to hierarchical linear modeling |
title_full | An introduction to hierarchical linear modeling |
title_fullStr | An introduction to hierarchical linear modeling |
title_full_unstemmed | An introduction to hierarchical linear modeling |
title_short | An introduction to hierarchical linear modeling |
title_sort | introduction to hierarchical linear modeling |
topic | Hierarchical Linear Models Nested Data Hypothesis Testing Parameter Estimation |
url | http://www.tqmp.org/Content/vol08-1/p052/p052.pdf |
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