Generalizing across stimuli as well as subjects: A non-mathematical tutorial on mixed-effects modelsﾠ
| dc.citation.firstpage | 201 | en_US |
| dc.citation.issueNumber | 3 | en_US |
| dc.citation.journalTitle | The Quantitative Methods for Psychology | en_US |
| dc.citation.lastpage | 219 | en_US |
| dc.citation.volumeNumber | 12 | en_US |
| dc.contributor.author | Chang, Yu-Hsuan A. | en_US |
| dc.contributor.author | Lane, David M. | en_US |
| dc.date.accessioned | 2016-11-22T15:16:07Z | en_US |
| dc.date.available | 2016-11-22T15:16:07Z | en_US |
| dc.date.issued | 2016 | en_US |
| dc.description.abstract | Although it has long been known that analyses that treat stimuli as a fixed effect do not permit generalization from the sample of stimuli to the population of stimuli, surprisingly little attention has been paid to this issue outside of the field of psycholinguistics. The purposes of the article are (a) to present a non-technical explanation of why it is critical to provide a statistical basis for generalizing to both the population subjects and the population of stimuli and (b) to provide instructions for doing analyses that allows this generalization using four common statistical analysis programs (JMP, R, SAS, and SPSS). | en_US |
| dc.identifier.citation | Chang, Yu-Hsuan A. and Lane, David M.. "Generalizing across stimuli as well as subjects: A non-mathematical tutorial on mixed-effects modelsﾠ." <i>The Quantitative Methods for Psychology,</i> 12, no. 3 (2016) The Quantitative Methods for Psychology: 201-219. http://dx.doi.org/10.20982/tqmp.12.3.p201ﾠ. | en_US |
| dc.identifier.doi | http://dx.doi.org/10.20982/tqmp.12.3.p201ﾠ | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/92714 | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | The Quantitative Methods for Psychology | en_US |
| dc.rights | This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.subject.keyword | mixed-effects models | en_US |
| dc.subject.keyword | tutorialsﾠ | en_US |
| dc.title | Generalizing across stimuli as well as subjects: A non-mathematical tutorial on mixed-effects modelsﾠ | en_US |
| dc.type | Journal article | en_US |
| dc.type.dcmi | Text | en_US |
| dc.type.publication | publisher version | en_US |
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