### Abstract

In contrast to the standard use of regression, in which an individual's score on the dependent variable is unknown, neuropsychologists are often interested in comparing a predicted score with a known obtained score. Existing inferential methods use the standard error for a new case (SN+1) to provide confidence limits on a predicted score and hence are tailored to the standard usage. However, SN+1 can be used to test whether the discrepancy between a patient's predicted and obtained scores was drawn from the distribution of discrepancies in a control population. This method simultaneously provides a point estimate of the percentage of the control population that would exhibit a larger discrepancy. A method for obtaining confidence limits on this percentage is also developed. These methods can be used with existing regression equations and are particularly useful when the sample used to generate a regression equation is modest in size. Monte Carlo simulations confirm the validity of the methods, and computer programs that implement them are described and made available.

Original language | English |
---|---|

Pages (from-to) | 259-271 |

Number of pages | 12 |

Journal | Neuropsychology |

Volume | 20 |

DOIs | |

Publication status | Published - 2006 |

### Keywords

- neuropsychological assessment
- regression equations
- single-case methods
- TRUAX RELIABLE CHANGE
- CLINICAL NEUROPSYCHOLOGY
- CLASSICAL APPROACH
- STANDARD ERROR
- WAIS-R
- INDEX
- PERFORMANCE
- JACOBSON

### Cite this

*Neuropsychology*,

*20*, 259-271. https://doi.org/10.1037/0894-4105.20.3.259

**Comparing patients’ predicted test scores from a regression equation with their obtained scores: a significance test and point estimate of abnormality with accompanying confidence limits.** / Crawford, John Robertson; Garthwaite, P. H.

Research output: Contribution to journal › Article

*Neuropsychology*, vol. 20, pp. 259-271. https://doi.org/10.1037/0894-4105.20.3.259

}

TY - JOUR

T1 - Comparing patients’ predicted test scores from a regression equation with their obtained scores: a significance test and point estimate of abnormality with accompanying confidence limits

AU - Crawford, John Robertson

AU - Garthwaite, P. H.

PY - 2006

Y1 - 2006

N2 - In contrast to the standard use of regression, in which an individual's score on the dependent variable is unknown, neuropsychologists are often interested in comparing a predicted score with a known obtained score. Existing inferential methods use the standard error for a new case (SN+1) to provide confidence limits on a predicted score and hence are tailored to the standard usage. However, SN+1 can be used to test whether the discrepancy between a patient's predicted and obtained scores was drawn from the distribution of discrepancies in a control population. This method simultaneously provides a point estimate of the percentage of the control population that would exhibit a larger discrepancy. A method for obtaining confidence limits on this percentage is also developed. These methods can be used with existing regression equations and are particularly useful when the sample used to generate a regression equation is modest in size. Monte Carlo simulations confirm the validity of the methods, and computer programs that implement them are described and made available.

AB - In contrast to the standard use of regression, in which an individual's score on the dependent variable is unknown, neuropsychologists are often interested in comparing a predicted score with a known obtained score. Existing inferential methods use the standard error for a new case (SN+1) to provide confidence limits on a predicted score and hence are tailored to the standard usage. However, SN+1 can be used to test whether the discrepancy between a patient's predicted and obtained scores was drawn from the distribution of discrepancies in a control population. This method simultaneously provides a point estimate of the percentage of the control population that would exhibit a larger discrepancy. A method for obtaining confidence limits on this percentage is also developed. These methods can be used with existing regression equations and are particularly useful when the sample used to generate a regression equation is modest in size. Monte Carlo simulations confirm the validity of the methods, and computer programs that implement them are described and made available.

KW - neuropsychological assessment

KW - regression equations

KW - single-case methods

KW - TRUAX RELIABLE CHANGE

KW - CLINICAL NEUROPSYCHOLOGY

KW - CLASSICAL APPROACH

KW - STANDARD ERROR

KW - WAIS-R

KW - INDEX

KW - PERFORMANCE

KW - JACOBSON

U2 - 10.1037/0894-4105.20.3.259

DO - 10.1037/0894-4105.20.3.259

M3 - Article

VL - 20

SP - 259

EP - 271

JO - Neuropsychology

JF - Neuropsychology

SN - 0894-4105

ER -