Document Detail


Analytical methods to detect within-individual changes in discounting.
MedLine Citation:
PMID:  20384429     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Discounting, as a quantifiable measure of impulsivity, is often estimated within individuals via nonlinear regression. Here, we describe how to directly estimate within-individual change of the discounting parameter between 2 conditions and subsequently statistically test for that change using the discounting data from a single individual. To date, there has been no systematic description of how to conduct such an analysis. Employing the method allows investigators and clinicians to evaluate whether a single individual has statistically changed the way he or she discounts between 2 conditions (e.g., in the absence or presence of a pharmacologic, different time points, different rewards, etc.). We further describe a meta-analytic approach for combining estimated changes in discounting from individuals in a sample to make population inference. By providing more precise population estimates, this approach increases statistical power over traditional analytic methods.
Authors:
Reid D Landes; Jeffery A Pitcock; Richard Yi; Warren K Bickel
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural    
Journal Detail:
Title:  Experimental and clinical psychopharmacology     Volume:  18     ISSN:  1936-2293     ISO Abbreviation:  Exp Clin Psychopharmacol     Publication Date:  2010 Apr 
Date Detail:
Created Date:  2010-04-13     Completed Date:  2010-07-01     Revised Date:  2014-08-27    
Medline Journal Info:
Nlm Unique ID:  9419066     Medline TA:  Exp Clin Psychopharmacol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  175-83     Citation Subset:  IM    
Copyright Information:
2010 APA, all rights reserved
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MeSH Terms
Descriptor/Qualifier:
Data Interpretation, Statistical*
Humans
Impulsive Behavior / psychology*
Individuality*
Meta-Analysis as Topic
Models, Statistical
Psychometrics / methods*
Research Design
Grant Support
ID/Acronym/Agency:
K02 DA034767/DA/NIDA NIH HHS; L30 DA021964/DA/NIDA NIH HHS; R01 DA11692/DA/NIDA NIH HHS
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