The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models

Thumbnail Image
Date
2019
Editors
Contact
Journal ISSN
Electronic ISSN
ISBN
Bibliographical data
Publisher
Series
DOI (citable link)
ArXiv-ID
International patent number
Link to the license
EU project number
Project
Open Access publication
Collections
Restricted until
Title in another language
Research Projects
Organizational Units
Journal Issue
Publication type
Journal article
Publication status
Published
Published in
Frontiers in Psychology ; 10 (2019). - 1067. - eISSN 1664-1078
Abstract
In educational psychology, observational units are oftentimes nested within superordinate groups. Researchers need to account for hierarchy in the data by means of multilevel modeling, but especially in three-level longitudinal models, it is often unclear which sample size is necessary for reliable parameter estimation. To address this question, we generated a population dataset based on a study in the field of educational psychology, consisting of 3000 classrooms (level-3) with 55000 students (level-2) measured at 5 occasions (level-1), including predictors on each level and interaction effects. Drawing from this data, we realized 1000 random samples each for various sample and missing value conditions and compared analysis results with the true population parameters. We found that sampling at least 15 level-2 units each in 35 level-3 units results in unbiased fixed effects estimates, whereas higher-level random effects variance estimates require larger samples. Overall, increasing the level-2 sample size most strongly improves estimation soundness. We further discuss how data characteristics influence parameter estimation and provide specific sample size recommendations.
Summary in another language
Subject (DDC)
150 Psychology
Keywords
Conference
Review
undefined / . - undefined, undefined. - (undefined; undefined)
Cite This
ISO 690KERKHOFF, Denise, Fridtjof W. NUSSBECK, 2019. The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models. In: Frontiers in Psychology. 10, 1067. eISSN 1664-1078. Available under: doi: 10.3389/fpsyg.2019.01067
BibTex
@article{Kerkhoff2019-05-21Influ-45944,
  year={2019},
  doi={10.3389/fpsyg.2019.01067},
  title={The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models},
  volume={10},
  journal={Frontiers in Psychology},
  author={Kerkhoff, Denise and Nussbeck, Fridtjof W.},
  note={Article Number: 1067}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/45944">
    <dc:rights>Attribution 4.0 International</dc:rights>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-06-05T12:39:16Z</dc:date>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/45944/1/Kerkhoff_2-10h3esfj2wt733.pdf"/>
    <dcterms:issued>2019-05-21</dcterms:issued>
    <dc:contributor>Kerkhoff, Denise</dc:contributor>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/45944/1/Kerkhoff_2-10h3esfj2wt733.pdf"/>
    <dcterms:abstract xml:lang="eng">In educational psychology, observational units are oftentimes nested within superordinate groups. Researchers need to account for hierarchy in the data by means of multilevel modeling, but especially in three-level longitudinal models, it is often unclear which sample size is necessary for reliable parameter estimation. To address this question, we generated a population dataset based on a study in the field of educational psychology, consisting of 3000 classrooms (level-3) with 55000 students (level-2) measured at 5 occasions (level-1), including predictors on each level and interaction effects. Drawing from this data, we realized 1000 random samples each for various sample and missing value conditions and compared analysis results with the true population parameters. We found that sampling at least 15 level-2 units each in 35 level-3 units results in unbiased fixed effects estimates, whereas higher-level random effects variance estimates require larger samples. Overall, increasing the level-2 sample size most strongly improves estimation soundness. We further discuss how data characteristics influence parameter estimation and provide specific sample size recommendations.</dcterms:abstract>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/43"/>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/45944"/>
    <dc:contributor>Nussbeck, Fridtjof W.</dc:contributor>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-06-05T12:39:16Z</dcterms:available>
    <dc:creator>Kerkhoff, Denise</dc:creator>
    <dcterms:title>The Influence of Sample Size on Parameter Estimates in Three-Level Random-Effects Models</dcterms:title>
    <dc:creator>Nussbeck, Fridtjof W.</dc:creator>
    <dc:language>eng</dc:language>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by/4.0/"/>
  </rdf:Description>
</rdf:RDF>
Internal note
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Contact
URL of original publication
Test date of URL
Examination date of dissertation
Method of financing
Comment on publication
Alliance license
Corresponding Authors der Uni Konstanz vorhanden
International Co-Authors
Bibliography of Konstanz
Yes
Refereed
Yes