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The impact of different estimation procedures on net monetary benefit in clinical trials
Descriptive
TypeOfResource
Text
TitleInfo
(ID = T-1)
Title
The impact of different estimation procedures on net monetary benefit in clinical trials
SubTitle
a simulation study
Identifier
ETD_1240
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000054805
Language
LanguageTerm
(authority = ISO639-2);
(type = code)
eng
Genre
(authority = marcgt)
theses
Subject
(ID = SBJ-1);
(authority = RUETD)
Topic
Public Health
Subject
(ID = SBJ-2);
(authority = ETD-LCSH)
Topic
Medical care, Cost of
Subject
(ID = SBJ-3);
(authority = ETD-LCSH)
Topic
Medical care--Cost effectiveness
Subject
(ID = SBJ-4);
(authority = ETD-LCSH)
Topic
Clinical trials
Abstract
(type = abstract)
Background: Growth in health care spending has led to greater use of cost-effectiveness analysis (CEA) in assessing health technologies. Traditional CEA uses the incremental cost-effectiveness ratio (ICER), a measure with statistical issues and limitations with missing data. Better analytic methods for CEA are needed to inform health care policy decisions. Objectives: The study evaluated estimates of cost-effectiveness from three models using incremental net monetary benefit (INMB) rather than ICER. Estimates were compared under different conditions of missingness. Data were simulated to include missing at random (MAR) and missing not at random (MNAR) nonresponse mechanisms as defined by Little and Rubin (2002). Methods: The parameter of interest was INMB. Models were ANCOVA, mixed effects (ME), and joint mixed effects and log of time-to-dropout (joint ME), a selection model. Because the joint ME model incorporates correlation between time-to-dropout and random effects of the longitudinal model of NMB into one model, the hypothesis was it would produce the best estimate. Simulated treatment effect provided a “true” INMB for model evaluations that included bias (absolute difference from “true”), precision (ratio of variances), and cost-effectiveness acceptability curves with willingness-to-pay (λ) values from $0 to $100k. Base case used a threshold criterion for dropout. Sensitivity analyses assessed impact of higher missingness. Post-hoc analysis used a trajectory criterion for dropout. Results: Base case analyses resulted in ANCOVA and ME models producing the least biased estimates. At λ = $50k, bias was $1.3k, $1.4k, and $2.3k, and precision was 1.27, 0.90, and 1.24 for ME, ANCOVA, and joint ME, respectively. ANCOVA estimates were best in sensitivity analyses although estimates were poor. The joint ME model performed best in the post hoc analysis. Conclusions: The models performed differently under alternative missingness conditions and were sensitive to nonresponse mechanisms. All estimates were poor when missingness was high, therefore, primary prevention of missing data should be a goal of research. MNAR nonresponse mechanisms are more complicated than implied by Little and Rubin’s definitions as shown by results with threshold versus trajectory criteria for dropout. Further research is needed with selection models in CEA and INMB as the measure of cost-effectiveness.
PhysicalDescription
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electronic resource
Extent
x, 282 p. : ill.
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application/pdf
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text/xml
Note
(type = degree)
Ph.D.
Note
Includes abstract
Note
Vita
Note
(type = bibliography)
Includes bibliographical references
Note
(type = statement of responsibility)
by Luella Marie Engelhart
Name
(ID = NAME-1);
(type = personal)
NamePart
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Engelhart
NamePart
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Luella
Role
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author
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Luella Engelhart
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NamePart
(type = family)
Rhoads
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(type = given)
George
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(authority = RULIB)
chair
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Advisory Committee
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George Rhoads
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(type = personal)
NamePart
(type = family)
Ohman-Strickland
NamePart
(type = given)
Pamela
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internal member
Affiliation
Advisory Committee
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Pamela Ohman-Strickland
Name
(ID = NAME-4);
(type = personal)
NamePart
(type = family)
Suh
NamePart
(type = given)
Dong-Churl
Role
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(authority = RULIB)
internal member
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Advisory Committee
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Dong-Churl Suh
Name
(ID = NAME-5);
(type = personal)
NamePart
(type = family)
Russell
NamePart
(type = given)
Louise
Role
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(authority = RULIB)
outside member
Affiliation
Advisory Committee
DisplayForm
Louise Russell
Name
(ID = NAME-1);
(type = corporate)
NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
(ID = NAME-2);
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NamePart
Graduate School - New Brunswick
Role
RoleTerm
(authority = RULIB)
school
OriginInfo
DateCreated
(qualifier = exact)
2008
DateOther
(qualifier = exact);
(type = degree)
2008
Place
PlaceTerm
(type = code)
xx
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
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3DF6R5X
Genre
(authority = ExL-Esploro)
ETD doctoral
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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
Engelhart
GivenName
Luella
Role
Copyright Holder
RightsEvent
(ID = RE-1);
(AUTHORITY = rulib)
Type
Permission or license
DateTime
2008-09-30 13:32:56
AssociatedEntity
(ID = AE-1);
(AUTHORITY = rulib)
Role
Copyright holder
Name
Luella Engelhart
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
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(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.
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Technical
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ETD
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application/pdf
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application/x-tar
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1761280
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Statistical Profile