View in EDS

Measurement Error and Equating Error in Power Analysis

Saved in:
Bibliographic Details
Title: Measurement Error and Equating Error in Power Analysis
Language: English
Authors: Phillips, Gary W., Jiang, Tao
Source: Practical Assessment, Research & Evaluation. Aug 2016 21(9).
Availability: Center for Educational Assessment. 813 North Pleasant Street, Amherst, MA 01002. e-mail: pare@umass.edu; Tel: 413-577-2180; Web site: https://scholarworks.umass.edu/pare
Peer Reviewed: Y
Page Count: 12
Publication Date: 2016
Document Type: Journal Articles
Reports - Research
Descriptors: Error of Measurement, Statistical Analysis, Equated Scores, Sample Size, Probability, Statistics, Error Correction, Correlation, True Scores
ISSN: 1531-7714
Abstract: Power analysis is a fundamental prerequisite for conducting scientific research. Without power analysis the researcher has no way of knowing whether the sample size is large enough to detect the effect he or she is looking for. This paper demonstrates how psychometric factors such as measurement error and equating error affect the power of statistical tests. The overall finding is that measurement error and equating error reduce power and inflate sample size requirements. It is recommended that researchers, where appropriate, incorporate these sources of error in conducting power analysis. If either of these two sources of error are present in the data but not accounted for in the power analysis, then power will be underestimated and sample size requirements will be underestimated.
Abstractor: As Provided
Entry Date: 2016
Accession Number: EJ1110578
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1110578
    Name: ERIC Full Text
    Category: fullText
    Text: Full Text from ERIC
Header DbId: eric
DbLabel: ERIC
An: EJ1110578
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Measurement Error and Equating Error in Power Analysis
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Phillips%2C+Gary+W%2E%22">Phillips, Gary W.</searchLink><br /><searchLink fieldCode="AR" term="%22Jiang%2C+Tao%22">Jiang, Tao</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Practical+Assessment%2C+Research+%26+Evaluation%22"><i>Practical Assessment, Research & Evaluation</i></searchLink>. Aug 2016 21(9).
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Center for Educational Assessment. 813 North Pleasant Street, Amherst, MA 01002. e-mail: pare@umass.edu; Tel: 413-577-2180; Web site: https://scholarworks.umass.edu/pare
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 12
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2016
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Error+of+Measurement%22">Error of Measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+Analysis%22">Statistical Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Equated+Scores%22">Equated Scores</searchLink><br /><searchLink fieldCode="DE" term="%22Sample+Size%22">Sample Size</searchLink><br /><searchLink fieldCode="DE" term="%22Probability%22">Probability</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Error+Correction%22">Error Correction</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22True+Scores%22">True Scores</searchLink>
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1531-7714
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Power analysis is a fundamental prerequisite for conducting scientific research. Without power analysis the researcher has no way of knowing whether the sample size is large enough to detect the effect he or she is looking for. This paper demonstrates how psychometric factors such as measurement error and equating error affect the power of statistical tests. The overall finding is that measurement error and equating error reduce power and inflate sample size requirements. It is recommended that researchers, where appropriate, incorporate these sources of error in conducting power analysis. If either of these two sources of error are present in the data but not accounted for in the power analysis, then power will be underestimated and sample size requirements will be underestimated.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2016
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1110578
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1110578
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 12
    Subjects:
      – SubjectFull: Error of Measurement
        Type: general
      – SubjectFull: Statistical Analysis
        Type: general
      – SubjectFull: Equated Scores
        Type: general
      – SubjectFull: Sample Size
        Type: general
      – SubjectFull: Probability
        Type: general
      – SubjectFull: Statistics
        Type: general
      – SubjectFull: Error Correction
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: True Scores
        Type: general
    Titles:
      – TitleFull: Measurement Error and Equating Error in Power Analysis
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Phillips, Gary W.
      – PersonEntity:
          Name:
            NameFull: Jiang, Tao
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 08
              Type: published
              Y: 2016
          Identifiers:
            – Type: issn-electronic
              Value: 1531-7714
          Numbering:
            – Type: volume
              Value: 21
            – Type: issue
              Value: 9
          Titles:
            – TitleFull: Practical Assessment, Research & Evaluation
              Type: main
ResultId 1