Accuracy of Regression Equation Prediction Across the Range of EstimatedPremorbid IQ.
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| Title: | Accuracy of Regression Equation Prediction Across the Range of EstimatedPremorbid IQ. |
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| Authors: | Graves, Roger E. |
| Source: | Journal of Clinical & Experimental Neuropsychology. Jun2000, Vol. 22 Issue 3, p316. 9p. |
| Subjects: | Intelligence levels, Regression analysis |
| Abstract: | Linear regression is often used to predict psychological criterion variables such as premorbid IQ. The prevailing method of evaluating the accuracy of prediction indicates poor accuracy for both high and low criterion values. These results have led to the conclusion that the equations are not applicable for predicting scores beyond about one standard deviation from the mean. The apparent inaccuracy at the extremes, however, is an artifact of inappropriate analysis. An alternative analysis method is described and used to re-analyze two sets of data. Empirical results show that both high and low WAIS-R IQ scores, predicted using versions of the NART, agree with actual measured IQ scores as accurately as do predicted scores near the mean. In addition, confidence intervals were only 5% larger for more extreme predicted values than for values near the mean, which would be of minor clinical consequence. The practical constraint on prediction of extreme values arises not from the regression technique, but from the limited range of the predictor variable(s). The two reviewed IQ prediction equations would, however, have adequate range for a high percentage of individuals. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Clinical & Experimental Neuropsychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 4561510 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Accuracy of Regression Equation Prediction Across the Range of EstimatedPremorbid IQ. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Graves%2C+Roger+E%2E%22">Graves, Roger E.</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Clinical+%26+Experimental+Neuropsychology%22">Journal of Clinical & Experimental Neuropsychology</searchLink>. Jun2000, Vol. 22 Issue 3, p316. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Intelligence+levels%22">Intelligence levels</searchLink><br /><searchLink fieldCode="DE" term="%22Regression+analysis%22">Regression analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Linear regression is often used to predict psychological criterion variables such as premorbid IQ. The prevailing method of evaluating the accuracy of prediction indicates poor accuracy for both high and low criterion values. These results have led to the conclusion that the equations are not applicable for predicting scores beyond about one standard deviation from the mean. The apparent inaccuracy at the extremes, however, is an artifact of inappropriate analysis. An alternative analysis method is described and used to re-analyze two sets of data. Empirical results show that both high and low WAIS-R IQ scores, predicted using versions of the NART, agree with actual measured IQ scores as accurately as do predicted scores near the mean. In addition, confidence intervals were only 5% larger for more extreme predicted values than for values near the mean, which would be of minor clinical consequence. The practical constraint on prediction of extreme values arises not from the regression technique, but from the limited range of the predictor variable(s). The two reviewed IQ prediction equations would, however, have adequate range for a high percentage of individuals. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Clinical & Experimental Neuropsychology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1076/1380-3395(200006)22:3;1-V;FT316 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 316 Subjects: – SubjectFull: Intelligence levels Type: general – SubjectFull: Regression analysis Type: general Titles: – TitleFull: Accuracy of Regression Equation Prediction Across the Range of EstimatedPremorbid IQ. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Graves, Roger E. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2000 Type: published Y: 2000 Identifiers: – Type: issn-print Value: 13803395 Numbering: – Type: volume Value: 22 – Type: issue Value: 3 Titles: – TitleFull: Journal of Clinical & Experimental Neuropsychology Type: main |
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