View in EDS PDF Full Text

The Guttman errors as a tool for response shift detection at subgroup and item levels.

Saved in:
Bibliographic Details
Title: The Guttman errors as a tool for response shift detection at subgroup and item levels.
Authors: Blanchin, Myriam, Sébille, Véronique, Guilleux, Alice, Hardouin, Jean-Benoit, Sébille, Véronique (AUTHOR)
Source: Quality of Life Research. Jun2016, Vol. 25 Issue 6, p1385-1393. 9p.
Subjects: Quality of life, Guttman scale, Item response theory, Algorithms, Statistics, Mental health, Comparative studies, Health status indicators, Mathematical models, Research methodology, Medical cooperation, Sensory perception, Questionnaires, Research, Sickness Impact Profile, Theory, Evaluation research
Abstract: Purpose: Statistical methods for identifying response shift (RS) at the individual level could be of great practical value in interpreting change in PRO data. Guttman errors (GE) may help to identify discrepancies in respondent's answers to items compared to an expected response pattern and to identify subgroups of patients that are more likely to present response shift. This study explores the benefits of using a GE-based method for RS detection at the subgroup and item levels.Methods: The analysis was performed on the SatisQoL study. The number of GE was determined for each individual at each time of measurement (at baseline T0 and 6 months after discharge M6). Individuals showing discrepancies (with many GE) were suspected to interpret the items differently from the majority of the sample. Patients having a large number of GE at M6 only and not at T0 were assumed to present RS. Patients having a small number of GE at T0 and M6 were assumed to present no RS. The RespOnse Shift ALgorithm in Item response theory (ROSALI) was then applied on the whole sample and on both groups.Results: Different types of RS (non-uniform recalibration, reprioritization) were more prevalent in the group composed of patients assumed to present RS based on GE. On the opposite, no RS was detected on patients having few GE.Conclusions: Guttman errors and item response theory models seem to be relevant tools to discriminate individuals affected by RS from the others at the item level. [ABSTRACT FROM AUTHOR]
Copyright of Quality of Life Research is the property of Springer Nature 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
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 115397968
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: The Guttman errors as a tool for response shift detection at subgroup and item levels.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Blanchin%2C+Myriam%22">Blanchin, Myriam</searchLink><br /><searchLink fieldCode="AR" term="%22Sébille%2C+Véronique%22">Sébille, Véronique</searchLink><br /><searchLink fieldCode="AR" term="%22Guilleux%2C+Alice%22">Guilleux, Alice</searchLink><br /><searchLink fieldCode="AR" term="%22Hardouin%2C+Jean-Benoit%22">Hardouin, Jean-Benoit</searchLink><br /><searchLink fieldCode="AR" term="%22Sébille%2C+Véronique%22">Sébille, Véronique</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Quality+of+Life+Research%22">Quality of Life Research</searchLink>. Jun2016, Vol. 25 Issue 6, p1385-1393. 9p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Quality+of+life%22">Quality of life</searchLink><br /><searchLink fieldCode="DE" term="%22Guttman+scale%22">Guttman scale</searchLink><br /><searchLink fieldCode="DE" term="%22Item+response+theory%22">Item response theory</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health%22">Mental health</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+studies%22">Comparative studies</searchLink><br /><searchLink fieldCode="DE" term="%22Health+status+indicators%22">Health status indicators</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+models%22">Mathematical models</searchLink><br /><searchLink fieldCode="DE" term="%22Research+methodology%22">Research methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+cooperation%22">Medical cooperation</searchLink><br /><searchLink fieldCode="DE" term="%22Sensory+perception%22">Sensory perception</searchLink><br /><searchLink fieldCode="DE" term="%22Questionnaires%22">Questionnaires</searchLink><br /><searchLink fieldCode="DE" term="%22Research%22">Research</searchLink><br /><searchLink fieldCode="DE" term="%22Sickness+Impact+Profile%22">Sickness Impact Profile</searchLink><br /><searchLink fieldCode="DE" term="%22Theory%22">Theory</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+research%22">Evaluation research</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: <bold>Purpose: </bold>Statistical methods for identifying response shift (RS) at the individual level could be of great practical value in interpreting change in PRO data. Guttman errors (GE) may help to identify discrepancies in respondent's answers to items compared to an expected response pattern and to identify subgroups of patients that are more likely to present response shift. This study explores the benefits of using a GE-based method for RS detection at the subgroup and item levels.<bold>Methods: </bold>The analysis was performed on the SatisQoL study. The number of GE was determined for each individual at each time of measurement (at baseline T0 and 6 months after discharge M6). Individuals showing discrepancies (with many GE) were suspected to interpret the items differently from the majority of the sample. Patients having a large number of GE at M6 only and not at T0 were assumed to present RS. Patients having a small number of GE at T0 and M6 were assumed to present no RS. The RespOnse Shift ALgorithm in Item response theory (ROSALI) was then applied on the whole sample and on both groups.<bold>Results: </bold>Different types of RS (non-uniform recalibration, reprioritization) were more prevalent in the group composed of patients assumed to present RS based on GE. On the opposite, no RS was detected on patients having few GE.<bold>Conclusions: </bold>Guttman errors and item response theory models seem to be relevant tools to discriminate individuals affected by RS from the others at the item level. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Quality of Life Research is the property of Springer Nature 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=115397968
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s11136-016-1268-8
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 1385
    Subjects:
      – SubjectFull: Quality of life
        Type: general
      – SubjectFull: Guttman scale
        Type: general
      – SubjectFull: Item response theory
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Mental health
        Type: general
      – SubjectFull: Comparative studies
        Type: general
      – SubjectFull: Health status indicators
        Type: general
      – SubjectFull: Mathematical models
        Type: general
      – SubjectFull: Research methodology
        Type: general
      – SubjectFull: Medical cooperation
        Type: general
      – SubjectFull: Sensory perception
        Type: general
      – SubjectFull: Questionnaires
        Type: general
      – SubjectFull: Research
        Type: general
      – SubjectFull: Sickness Impact Profile
        Type: general
      – SubjectFull: Theory
        Type: general
      – SubjectFull: Evaluation research
        Type: general
    Titles:
      – TitleFull: The Guttman errors as a tool for response shift detection at subgroup and item levels.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Blanchin, Myriam
      – PersonEntity:
          Name:
            NameFull: Sébille, Véronique
      – PersonEntity:
          Name:
            NameFull: Guilleux, Alice
      – PersonEntity:
          Name:
            NameFull: Hardouin, Jean-Benoit
      – PersonEntity:
          Name:
            NameFull: Sébille, Véronique
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: Jun2016
              Type: published
              Y: 2016
          Identifiers:
            – Type: issn-print
              Value: 09629343
          Numbering:
            – Type: volume
              Value: 25
            – Type: issue
              Value: 6
          Titles:
            – TitleFull: Quality of Life Research
              Type: main
ResultId 1