Testing Interactions in Multinomial Processing Tree Models
Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects. In this paper, we adopt the interaction concept as defined in...
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| Published in | Frontiers in psychology Vol. 10; p. 2364 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Frontiers Media S.A
01.11.2019
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| Online Access | Get full text |
| ISSN | 1664-1078 1664-1078 |
| DOI | 10.3389/fpsyg.2019.02364 |
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| Abstract | Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects. In this paper, we adopt the interaction concept as defined in log-linear models and show why it is appropriate for MPT models. We then explain how to implement and test ordinal and disordinal two-way interaction hypotheses in MPT models. We also show how our method generalizes to higher-order interactions involving three or more factors. An empirical example from source memory and aging demonstrates the applicability of this method and allows for directly testing the associative deficit theory that age differences are larger in associative (e.g., source) memory as opposed to item memory. Throughout the paper, we explain how most analytic steps can be easily implemented in the freely available software multiTree.Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects. In this paper, we adopt the interaction concept as defined in log-linear models and show why it is appropriate for MPT models. We then explain how to implement and test ordinal and disordinal two-way interaction hypotheses in MPT models. We also show how our method generalizes to higher-order interactions involving three or more factors. An empirical example from source memory and aging demonstrates the applicability of this method and allows for directly testing the associative deficit theory that age differences are larger in associative (e.g., source) memory as opposed to item memory. Throughout the paper, we explain how most analytic steps can be easily implemented in the freely available software multiTree. |
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| AbstractList | Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects. In this paper, we adopt the interaction concept as defined in log-linear models and show why it is appropriate for MPT models. We then explain how to implement and test ordinal and disordinal two-way interaction hypotheses in MPT models. We also show how our method generalizes to higher-order interactions involving three or more factors. An empirical example from source memory and aging demonstrates the applicability of this method and allows for directly testing the associative deficit theory that age differences are larger in associative (e.g., source) memory as opposed to item memory. Throughout the paper, we explain how most analytic steps can be easily implemented in the freely available software multiTree.Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects. In this paper, we adopt the interaction concept as defined in log-linear models and show why it is appropriate for MPT models. We then explain how to implement and test ordinal and disordinal two-way interaction hypotheses in MPT models. We also show how our method generalizes to higher-order interactions involving three or more factors. An empirical example from source memory and aging demonstrates the applicability of this method and allows for directly testing the associative deficit theory that age differences are larger in associative (e.g., source) memory as opposed to item memory. Throughout the paper, we explain how most analytic steps can be easily implemented in the freely available software multiTree. Multinomial processing tree (MPT) models allow testing hypotheses on latent psychological processes that underlie human behavior. However, past applications of this model class have mainly been restricted to the analysis of main effects. In this paper, we adopt the interaction concept as defined in log-linear models and show why it is appropriate for MPT models. We then explain how to implement and test ordinal and disordinal two-way interaction hypotheses in MPT models. We also show how our method generalizes to higher-order interactions involving three or more factors. An empirical example from source memory and aging demonstrates the applicability of this method and allows for directly testing the associative deficit theory that age differences are larger in associative (e.g., source) memory as opposed to item memory. Throughout the paper, we explain how most analytic steps can be easily implemented in the freely available software multiTree. |
| Author | Kuhlmann, Beatrice G. Moshagen, Morten Erdfelder, Edgar |
| AuthorAffiliation | 2 Department of Psychology, Ulm University , Ulm , Germany 1 Department of Psychology, School of Social Sciences, University of Mannheim , Mannheim , Germany |
| AuthorAffiliation_xml | – name: 2 Department of Psychology, Ulm University , Ulm , Germany – name: 1 Department of Psychology, School of Social Sciences, University of Mannheim , Mannheim , Germany |
| Author_xml | – sequence: 1 givenname: Beatrice G. surname: Kuhlmann fullname: Kuhlmann, Beatrice G. – sequence: 2 givenname: Edgar surname: Erdfelder fullname: Erdfelder, Edgar – sequence: 3 givenname: Morten surname: Moshagen fullname: Moshagen, Morten |
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| Cites_doi | 10.1002/0471249688 10.1037/a0021055 10.1037/0033-295X.95.3.318 10.1037/0033-295X.87.4.375 10.3758/PBR.15.4.713 10.3758/BF03210812 10.1016/j.spl.2015.06.014 10.1007/978-1-4899-4541-9 10.1016/j.jmp.2009.06.007 10.1007/978-1-4612-4578-0 10.1037/0033-2909.114.1.3 10.1027/0044-3409.217.3.108 10.1007/BF02294263 10.1016/j.jmp.2004.03.002 10.1037//0278-7393.26.5.1170 10.1016/j.jmp.2009.06.005 10.3758/s13428-017-0869-7 10.1037/0033-295X.107.4.852 10.1027/0044-3409.215.1.61 10.1007/S11336-009-9141-0 10.3758/s13428-012-0259-0 10.1027/0044-3409.215.1.52 10.1037/0278-7393.22.1.197 10.1007/s11336-004-1188-3 10.1027/1618-3169/a000261 10.1007/s11336-013-9374-9 10.1080/17470218.2011.586708 10.3758/BF03207714 10.3758/BRM.42.1.42 10.3758/BF03193157 10.1111/j.2044-8317.1986.tb00852.x 10.3758/BF03197041 |
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| Copyright | Copyright © 2019 Kuhlmann, Erdfelder and Moshagen. Copyright © 2019 Kuhlmann, Erdfelder and Moshagen. 2019 Kuhlmann, Erdfelder and Moshagen |
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| SubjectTerms | associative deficit hypothesis cognitive aging interactions multinomial processing tree models parametric order constraints Psychology |
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| Title | Testing Interactions in Multinomial Processing Tree Models |
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