Individual differences make a difference: On the use and the psychometric properties of difference scores in social psychology
Much social psychological research is concerned with the question whether and how behavior changes because of a “treatment” (e.g., a situation that triggers a psychological reaction). One easy way to investigate such changes would be to analyze intraindividual differences before (Time 1) and after t...
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| Vydáno v: | European journal of social psychology Ročník 44; číslo 7; s. 673 - 682 |
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| Jazyk: | angličtina |
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Bognor Regis
Blackwell Publishing Ltd
01.12.2014
Wiley Subscription Services, Inc |
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| ISSN: | 0046-2772, 1099-0992 |
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| Abstract | Much social psychological research is concerned with the question whether and how behavior changes because of a “treatment” (e.g., a situation that triggers a psychological reaction). One easy way to investigate such changes would be to analyze intraindividual differences before (Time 1) and after the treatment (Time 2). Interestingly, many scholars refrain from using difference scores because they think they are inherently unreliable. However, the bad reputation of difference scores is, in many cases, unwarranted: difference scores can be sufficiently reliable when standard deviations differ between measurement occasions, and standard deviations are likely to differ between measurement occasions because of differential treatment effects (i.e., interindividual differences in responsiveness to a treatment) and/or “strong situation” treatments. In the present article, we will (1) summarize classic and current arguments regarding the reliability of difference scores, (2) discuss the use of residual change scores as an alternative to difference scores, and (3) argue that latent difference score models are a particularly useful tool that social psychologists should consider using more frequently. Copyright © 2014 John Wiley & Sons, Ltd. |
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| AbstractList | Much social psychological research is concerned with the question whether and how behavior changes because of a 'treatment' (e.g., a situation that triggers a psychological reaction). One easy way to investigate such changes would be to analyze intraindividual differences before (Time 1) and after the treatment (Time 2). Interestingly, many scholars refrain from using difference scores because they think they are inherently unreliable. However, the bad reputation of difference scores is, in many cases, unwarranted: difference scores can be sufficiently reliable when standard deviations differ between measurement occasions, and standard deviations are likely to differ between measurement occasions because of differential treatment effects (i.e., interindividual differences in responsiveness to a treatment) and/or 'strong situation' treatments. In the present article, we will (1) summarize classic and current arguments regarding the reliability of difference scores, (2) discuss the use of residual change scores as an alternative to difference scores, and (3) argue that latent difference score models are a particularly useful tool that social psychologists should consider using more frequently. Copyright © 2014 John Wiley & Sons, Ltd. Copyright John Wiley & Sons. Reproduced with permission. An electronic version of this article is available online at http://www.interscience.wiley.com Much social psychological research is concerned with the question whether and how behavior changes because of a 'treatment' (e.g., a situation that triggers a psychological reaction). One easy way to investigate such changes would be to analyze intraindividual differences before (Time 1) and after the treatment (Time 2). Interestingly, many scholars refrain from using difference scores because they think they are inherently unreliable. However, the bad reputation of difference scores is, in many cases, unwarranted: difference scores can be sufficiently reliable when standard deviations differ between measurement occasions, and standard deviations are likely to differ between measurement occasions because of differential treatment effects (i.e., interindividual differences in responsiveness to a treatment) and/or 'strong situation' treatments. In the present article, we will (1) summarize classic and current arguments regarding the reliability of difference scores, (2) discuss the use of residual change scores as an alternative to difference scores, and (3) argue that latent difference score models are a particularly useful tool that social psychologists should consider using more frequently. [Copyright John Wiley and Sons, Ltd.] Much social psychological research is concerned with the question whether and how behavior changes because of a "treatment" (e.g., a situation that triggers a psychological reaction). One easy way to investigate such changes would be to analyze intraindividual differences before (Time 1) and after the treatment (Time 2). Interestingly, many scholars refrain from using difference scores because they think they are inherently unreliable. However, the bad reputation of difference scores is, in many cases, unwarranted: difference scores can be sufficiently reliable when standard deviations differ between measurement occasions, and standard deviations are likely to differ between measurement occasions because of differential treatment effects (i.e., interindividual differences in responsiveness to a treatment) and/or "strong situation" treatments. In the present article, we will (1) summarize classic and current arguments regarding the reliability of difference scores, (2) discuss the use of residual change scores as an alternative to difference scores, and (3) argue that latent difference score models are a particularly useful tool that social psychologists should consider using more frequently. Much social psychological research is concerned with the question whether and how behavior changes because of a “treatment” (e.g., a situation that triggers a psychological reaction). One easy way to investigate such changes would be to analyze intraindividual differences before (Time 1) and after the treatment (Time 2). Interestingly, many scholars refrain from using difference scores because they think they are inherently unreliable. However, the bad reputation of difference scores is, in many cases, unwarranted: difference scores can be sufficiently reliable when standard deviations differ between measurement occasions, and standard deviations are likely to differ between measurement occasions because of differential treatment effects (i.e., interindividual differences in responsiveness to a treatment) and/or “strong situation” treatments. In the present article, we will (1) summarize classic and current arguments regarding the reliability of difference scores, (2) discuss the use of residual change scores as an alternative to difference scores, and (3) argue that latent difference score models are a particularly useful tool that social psychologists should consider using more frequently. Copyright © 2014 John Wiley & Sons, Ltd. |
| Author | Christ, Oliver Gollwitzer, Mario Lemmer, Gunnar |
| Author_xml | – sequence: 1 givenname: Mario surname: Gollwitzer fullname: Gollwitzer, Mario email: Correspondence to: Mario Gollwitzer, Philipps University Marburg, Department of Psychology, Gutenbergstrasse 18, 35032 Marburg, Germany., mario.gollwitzer@staff.uni-marburg.de organization: Department of Psychology, Philipps University Marburg, Marburg, Germany – sequence: 2 givenname: Oliver surname: Christ fullname: Christ, Oliver organization: Department of Psychology, Philipps University Marburg, Marburg, Germany – sequence: 3 givenname: Gunnar surname: Lemmer fullname: Lemmer, Gunnar organization: Department of Psychology, Philipps University Marburg, Marburg, Germany |
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| Title | Individual differences make a difference: On the use and the psychometric properties of difference scores in social psychology |
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