Effect size calculations and single subject designs
This study compared visual analyses with five alternative methods for assessing the magnitude of effect with single subject designs. Each method was successful in detecting intervention effect. When rank ordered, each method was consistent in identifying the participants with the largest effect. We...
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| Published in | Educational psychology (Dorchester-on-Thames) Vol. 25; no. 2-3; pp. 313 - 324 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Dorchester-on-Thames
Taylor and Francis Ltd
01.04.2005
Taylor & Francis Group Journals Taylor & Francis Ltd |
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| Online Access | Get full text |
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| Abstract | This study compared visual analyses with five alternative methods for assessing the magnitude of effect with single subject designs. Each method was successful in detecting intervention effect. When rank ordered, each method was consistent in identifying the participants with the largest effect. We recommend the use of the standard mean difference (SMD
all
) formula and we believe the use of a regression equation for calculating effect size in single subject data should be avoided. |
|---|---|
| AbstractList | This study compared visual analyses with five alternative methods for assessing the magnitude of effect with single subject designs. Each method was successful in detecting intervention effect. When rank ordered, each method was consistent in identifying the participants with the largest effect. We recommend the use of the standard mean difference (SMD
all
) formula and we believe the use of a regression equation for calculating effect size in single subject data should be avoided. This study compared visual analyses with five alternative methods for assessing the magnitude of effect with single subject designs. Each method was successful in detecting intervention effect. When rank ordered, each method was consistent in identifying the participants with the largest effect. We recommend the use of the standard mean difference (SMDall) formula and we believe the use of a regression equation for calculating effect size in single subject data should be avoided. [PUBLICATION ABSTRACT] This study compared visual analyses with five alternative methods for assessing the magnitude of effect with single subject designs. Each method was successful in detecting intervention effect. When rank ordered, each method was consistent in identifying the participants with the largest effect. We recommend the use of the standard mean difference (SMD[sub all]) formula and we believe the use of a regression equation for calculating effect size in single subject data should be avoided. |
| Author | Olive, Melissa L. Smith, Benjamin W. |
| Author_xml | – sequence: 1 givenname: Melissa L. surname: Olive fullname: Olive, Melissa L. email: molive@mail.utexas.edu organization: The University of Texas at Austin – sequence: 2 givenname: Benjamin W. surname: Smith fullname: Smith, Benjamin W. organization: The University of Texas at Austin |
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| Cites_doi | 10.1007/BF03391976 10.1080/02687030344000355 10.1007/BF02211821 10.1016/0005-7967(93)90115-B 10.1007/BF00962980 10.1016/S0005-7894(03)80013-8 10.1207/S15327035EX0904_5 10.1177/154079699001500307 10.1177/074193258700800206 10.1901/jaba.1994.27-197 10.1177/01454455980223001 10.1177/002246698501900404 10.1901/jaba.1968.1-175 |
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| Title | Effect size calculations and single subject designs |
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