### 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 |
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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