Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary Note
This paper explores the consequences of small cluster size for parameter estimation in multilevel models. In particular, the interest lies in parameter estimates (regression weights) in linear multilevel models of level 2 variables that are functions of level 1 variables, as for instance the cluste...
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| Format: | Article |
| Language: | English |
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GESIS - Leibniz-Institute for the Social Sciences, Mannheim
2016-06-01
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| Series: | Methoden, Daten, Analysen |
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| Online Access: | https://mda.gesis.org/index.php/mda/article/view/2016.005/48 |
| _version_ | 1828224677537906688 |
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| author | Reinhard Schunck |
| author_facet | Reinhard Schunck |
| author_sort | Reinhard Schunck |
| collection | DOAJ |
| description | This paper explores the consequences of small cluster size for parameter estimation in multilevel models. In particular, the interest lies in parameter estimates (regression weights) in linear multilevel models of level 2 variables that are functions of level 1 variables, as for instance the cluster-mean of a certain property, e.g. the average income or the proportion of certain people in a neighborhood. To this end, a simulation study is used to determine the
effect of varying cluster sizes and number of clusters. The results show that small cluster sizes can cause severe downward bias in estimated regression weights of aggregated level 2 variables. Bias does not decrease if the number of clusters (i.e. the level 2 units) increases. |
| first_indexed | 2024-04-12T17:21:54Z |
| format | Article |
| id | doaj.art-a0097a761b764a3e93ba4656b0203cf1 |
| institution | Directory Open Access Journal |
| issn | 1864-6956 2190-4936 |
| language | English |
| last_indexed | 2024-04-12T17:21:54Z |
| publishDate | 2016-06-01 |
| publisher | GESIS - Leibniz-Institute for the Social Sciences, Mannheim |
| record_format | Article |
| series | Methoden, Daten, Analysen |
| spelling | doaj.art-a0097a761b764a3e93ba4656b0203cf12022-12-22T03:23:27ZengGESIS - Leibniz-Institute for the Social Sciences, MannheimMethoden, Daten, Analysen1864-69562190-49362016-06-011019710910.12758/mda.2016.005Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary NoteReinhard Schunck0GESIS – Leibniz Institute for the Social SciencesThis paper explores the consequences of small cluster size for parameter estimation in multilevel models. In particular, the interest lies in parameter estimates (regression weights) in linear multilevel models of level 2 variables that are functions of level 1 variables, as for instance the cluster-mean of a certain property, e.g. the average income or the proportion of certain people in a neighborhood. To this end, a simulation study is used to determine the effect of varying cluster sizes and number of clusters. The results show that small cluster sizes can cause severe downward bias in estimated regression weights of aggregated level 2 variables. Bias does not decrease if the number of clusters (i.e. the level 2 units) increases.https://mda.gesis.org/index.php/mda/article/view/2016.005/48multilevel modelinghierarchical linear modelsample sizesurvey researchcluster sampling |
| spellingShingle | Reinhard Schunck Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary Note Methoden, Daten, Analysen multilevel modeling hierarchical linear model sample size survey research cluster sampling |
| title | Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary Note |
| title_full | Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary Note |
| title_fullStr | Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary Note |
| title_full_unstemmed | Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary Note |
| title_short | Cluster Size and Aggregated Level 2 Variables in Multilevel Models. A Cautionary Note |
| title_sort | cluster size and aggregated level 2 variables in multilevel models a cautionary note |
| topic | multilevel modeling hierarchical linear model sample size survey research cluster sampling |
| url | https://mda.gesis.org/index.php/mda/article/view/2016.005/48 |
| work_keys_str_mv | AT reinhardschunck clustersizeandaggregatedlevel2variablesinmultilevelmodelsacautionarynote |