View in EDS HTML Full Text PDF Full Text

Theory selection and evaluation in case series research.

Saved in:
Bibliographic Details
Title: Theory selection and evaluation in case series research.
Authors: Goldrick, Matthew (AUTHOR)
Source: Cognitive Neuropsychology. Oct2011, Vol. 28 Issue 7, p451-465. 15p. 1 Diagram, 1 Chart, 2 Graphs.
Subjects: Individual differences, Schwartz, M. F., Selection theorems, Empirical research, Simulation methods & models, Error analysis in mathematics
Abstract: Using empirical data to develop theories requires not only evaluating how well a theory accounts for data; it requires using the data to select the best theory from among a set of alternatives. Current case series research is examined in light of these two issues. Theory selection requires that theories make contrasting predictions. In the first section of this commentary, I present novel simulation results showing that existing theories of language production do not make contrasting predictions for the overall distribution of responses over a set of responses categories (e.g., correct response, semantic error, etc.; Dell, Schwartz, Martin, Saffran, & Gagnon, 1997). Given such results, in order to be theoretically productive case series research must focus on those aspects of data that serve to contrast theoretical alternatives. The second section considers evaluation of claims regarding individual differences. Such claims are typically underconstrained. Two approaches to addressing this issue are discussed. I argue that case series research should provide independent evidence for hypothesized individual differences. Second, parametric approaches might provide a means of constraining theories of individual differences. The plausibility of this approach is examined through novel analyses of empirical distributions of individual differences in impairments to lexical access (Schwartz, Dell, Martin, Gahl, & Sobel, 2006). [ABSTRACT FROM AUTHOR]
Copyright of Cognitive 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
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 93451056
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Theory selection and evaluation in case series research.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Goldrick%2C+Matthew%22">Goldrick, Matthew</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Cognitive+Neuropsychology%22">Cognitive Neuropsychology</searchLink>. Oct2011, Vol. 28 Issue 7, p451-465. 15p. 1 Diagram, 1 Chart, 2 Graphs.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Individual+differences%22">Individual differences</searchLink><br /><searchLink fieldCode="DE" term="%22Schwartz%2C+M%2E+F%2E%22">Schwartz, M. F.</searchLink><br /><searchLink fieldCode="DE" term="%22Selection+theorems%22">Selection theorems</searchLink><br /><searchLink fieldCode="DE" term="%22Empirical+research%22">Empirical research</searchLink><br /><searchLink fieldCode="DE" term="%22Simulation+methods+%26+models%22">Simulation methods & models</searchLink><br /><searchLink fieldCode="DE" term="%22Error+analysis+in+mathematics%22">Error analysis in mathematics</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Using empirical data to develop theories requires not only evaluating how well a theory accounts for data; it requires using the data to select the best theory from among a set of alternatives. Current case series research is examined in light of these two issues. Theory selection requires that theories make contrasting predictions. In the first section of this commentary, I present novel simulation results showing that existing theories of language production do not make contrasting predictions for the overall distribution of responses over a set of responses categories (e.g., correct response, semantic error, etc.; Dell, Schwartz, Martin, Saffran, & Gagnon, 1997). Given such results, in order to be theoretically productive case series research must focus on those aspects of data that serve to contrast theoretical alternatives. The second section considers evaluation of claims regarding individual differences. Such claims are typically underconstrained. Two approaches to addressing this issue are discussed. I argue that case series research should provide independent evidence for hypothesized individual differences. Second, parametric approaches might provide a means of constraining theories of individual differences. The plausibility of this approach is examined through novel analyses of empirical distributions of individual differences in impairments to lexical access (Schwartz, Dell, Martin, Gahl, & Sobel, 2006). [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Cognitive 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=93451056
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/02643294.2012.675319
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 451
    Subjects:
      – SubjectFull: Individual differences
        Type: general
      – SubjectFull: Schwartz, M. F.
        Type: general
      – SubjectFull: Selection theorems
        Type: general
      – SubjectFull: Empirical research
        Type: general
      – SubjectFull: Simulation methods & models
        Type: general
      – SubjectFull: Error analysis in mathematics
        Type: general
    Titles:
      – TitleFull: Theory selection and evaluation in case series research.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Goldrick, Matthew
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 10
              Text: Oct2011
              Type: published
              Y: 2011
          Identifiers:
            – Type: issn-print
              Value: 02643294
          Numbering:
            – Type: volume
              Value: 28
            – Type: issue
              Value: 7
          Titles:
            – TitleFull: Cognitive Neuropsychology
              Type: main
ResultId 1