Using regression equations built from summary data in the neuropsychological assessment of the individual case.

Abstract

Regression equations have many useful roles in neuropsychological assessment. This article is based on the premise that there is a large reservoir of published data that could be used to build regression equations; these equations could then be used to test a wide variety of hypotheses concerning the functioning of individual cases. This resource is currently underused because (a) not all neuropsychologists are aware that equations can be built with only basic summary data for a sample and (b) the computations involved are tedious and prone to error. To overcome these barriers, the authors set out the steps required to build regression equations from sample summary statistics and the further steps required to compute the associated statistics for drawing inferences concerning an individual case. The authors also develop, describe, and make available computer programs that implement the methods. Although caveats attach to the use of the methods, these need to be balanced against pragmatic considerations and against the alternative of either entirely ignoring a pertinent data set or using it informally to provide a clinical "guesstimate."

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 66 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.