Staff View
Correction for guessing in the framework of the 3PL item response theory

Descriptive

TypeOfResource
Text
TitleInfo (ID = T-1)
Title
Correction for guessing in the framework of the 3PL item response theory
Identifier
ETD_2624
Identifier (type = hdl)
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000053033
Language
LanguageTerm (authority = ISO639-2); (type = code)
eng
Genre (authority = marcgt)
theses
Subject (ID = SBJ-1); (authority = RUETD)
Topic
Education
Subject (ID = SBJ-2); (authority = ETD-LCSH)
Topic
Item response theory
Subject (ID = SBJ-3); (authority = ETD-LCSH)
Topic
Ability--Testing
Abstract (type = abstract)
Guessing behavior is an important topic with regard to assessing proficiency on multiple choice tests, particularly for examinees at lower levels of proficiency due to greater the potential for systematic error or bias which that inflates observed test scores. Methods that incorporate a correction for guessing on high-stakes tests generally rely on a scoring model that aims to minimize the potential benefit of guessing. In some cases, a formula score based on classical test theory (CTT) is applied with the intention of eliminating the influence of guessing from the number-right score (e.g., Holzinger, 1924). However, since its inception, significant controversy has surrounded the use and consequences associated with classical methods of correcting for guessing. More recently, item response theory (IRT) has been used to conceptualize and describe the effects of guessing. Yet CTT remains a dominant aspect of many assessment programs, and IRT models are rarely used for estimating proficiency with MC items – where guessing is most likely to exert an influence. Although there has been tremendous growth in the research of formal modeling based on IRT with respect to guessing, none of these IRT approaches have had widespread application. This dissertation provides a conceptual analysis of how the ―correction for guessing works within the framework of a 3PL model, and two new guessing correction formulas based on IRT are derived for improving observed score estimates. To demonstrate the utility of the new formula scores, they are applied as conditioning variable in two different approaches to DIF: the Mantel-Haenszel and logistic regression procedures. Two IRT formula scores were developed using Taylor approximations. Each of these formula scores requires the use of sample statistics in lieu of IRT parameters for estimating corrected true scores, and these statistics were obtained in two different ways that are referred to as the pseudo-Bayes and conditional probability methods. It is shown that the IRT formula scores adjust the number-correct score based on both the proficiency of an examinees and the examinee‘s pattern of responses across items. In two different simulation studies, the classical formula score performed better in terms of bias statistics, but the IRT formula scores had notable improvement in bias and r2 statistics compared to the number-correct score. The advantage of the IRT formula scores accounted for about 10% more of the variance in corrected true scores in the first quartile. Results also suggested that not much information lost due to the use of Taylor approximation. The pseudo-Bayes and conditional probabilities methods also resulted in little information loss. When applied to DIF analyses, the IRT formula scores had lower bias in both the log-odds ratios and type 1 error rates compared to the number-corrected score. Overall, the IRT formula scores decreased bias in the log-odds ratio by about 6% and in the type 1 error rate by about 10%.
PhysicalDescription
Form (authority = gmd)
electronic resource
Extent
xii, 141 p. : ill.
InternetMediaType
application/pdf
InternetMediaType
text/xml
Note (type = degree)
Ph.D.
Note
Includes abstract
Note
Vita
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Ting-Wei Chiu
Name (ID = NAME-1); (type = personal)
NamePart (type = family)
Chiu
NamePart (type = given)
Ting-Wei
NamePart (type = date)
1976-
Role
RoleTerm (authority = RULIB)
author
DisplayForm
Ting-Wei Chiu
Name (ID = NAME-2); (type = personal)
NamePart (type = family)
Camilli
NamePart (type = given)
Gregory A.
Role
RoleTerm (authority = RULIB)
chair
Affiliation
Advisory Committee
DisplayForm
Gregory A. Camilli
Name (ID = NAME-3); (type = personal)
NamePart (type = family)
Penfield
NamePart (type = given)
Douglas A.
Role
RoleTerm (authority = RULIB)
internal member
Affiliation
Advisory Committee
DisplayForm
Douglas A. Penfield
Name (ID = NAME-4); (type = personal)
NamePart (type = family)
Chiu
NamePart (type = given)
Chia-Yi
Role
RoleTerm (authority = RULIB)
internal member
Affiliation
Advisory Committee
DisplayForm
Chia-Yi Chiu
Name (ID = NAME-5); (type = personal)
NamePart (type = family)
Nichols
NamePart (type = given)
Paul
Role
RoleTerm (authority = RULIB)
outside member
Affiliation
Advisory Committee
DisplayForm
Paul Nichols
Name (ID = NAME-1); (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (ID = NAME-2); (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
OriginInfo
DateCreated (qualifier = exact)
2010
DateOther (qualifier = exact); (type = degree)
2010-05
Place
PlaceTerm (type = code)
xx
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Identifier (type = doi)
doi:10.7282/T3668D8M
Back to the top

Rights

RightsDeclaration (AUTHORITY = GS); (ID = rulibRdec0006)
The author owns the copyright to this work.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
RightsHolder (ID = PRH-1); (type = personal)
Name
FamilyName
Chiu
GivenName
Ting-Wei
Role
Copyright Holder
RightsEvent (ID = RE-1); (AUTHORITY = rulib)
Type
Permission or license
DateTime
2010-04-15 09:53:57
AssociatedEntity (ID = AE-1); (AUTHORITY = rulib)
Role
Copyright holder
Name
Ting-Wei Chiu
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject (ID = AO-1); (AUTHORITY = rulib)
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Back to the top

Technical

ContentModel
ETD
MimeType (TYPE = file)
application/pdf
MimeType (TYPE = container)
application/x-tar
FileSize (UNIT = bytes)
1699840
Checksum (METHOD = SHA1)
7f3a8030a7b986836902ca00f28a18f7985530ac
Back to the top
Version 8.3.13
Rutgers University Libraries - Copyright ©2020