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Design of primary and sensitivity analyses for handling non-future dependence missing data in clinical trials with an emphasis on the type-i error rate using multiple imputation and pattern mixture model approach
Descriptive
TitleInfo
Title
Design of primary and sensitivity analyses for handling non-future dependence missing data in clinical trials with an emphasis on the type-i error rate using multiple imputation and pattern mixture model approach
Name
(type = personal)
NamePart
(type = family)
Peng
NamePart
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Lixian
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Lixian Peng
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(authority = RULIB)
author
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(type = personal)
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Shih
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(type = given)
Weichung Joe
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Weichung Joe Shih
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Advisory Committee
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chair
Name
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LIN
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(type = given)
YONG
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YONG LIN
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Lu
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(type = given)
Shou-En
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Shou-En Lu
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Advisory Committee
Role
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(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Quan
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(type = given)
Hui
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Hui Quan
Affiliation
Advisory Committee
Role
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(authority = RULIB)
outside member
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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(authority = RULIB)
school
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Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
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2015
DateOther
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(type = degree)
2015-05
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2015
Place
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xx
Language
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(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
Missing data is a common problem in longitudinal clinical trials. Substantial missing data could introduce potential biases and undermine the scientific credibility of causal conclusions from clinical trials. To handle the missing data issue, it is always required by the regulatory agencies to pre-specify a primary analysis and sensitivity analysis in protocol or statistical analysis plan (SAP). Recent National Research Council (NRC) report questioned the reasonableness of the missing at random (MAR) setting as the primary analysis since MAR is a very special and doubtful assumption for the missing data mechanism, and the report encourages to use not missing at random (NMAR) setting as the primary analysis. One of the NMAR mechanisms is non-future dependence missing data (NFD-NMAR). It is also one of the recommended methods in the NRC report. This dissertation addressed this issue and proposed a process to investigate the mean-shift model with NFD-NMAR mechanism (NFD-Delta method). The goal is to provide, via the investigation process, a method of finding an appropriate shift parameter to specify the primary NMAR analysis in study protocol or SAP based on the maintenance of the type-I error rate for any late phase trial by simulations. The simulation set-up should be based on either early phase data or information from interim data of the current trial. The shift parameter of the NFD-Delta method constitutes the sensitivity analysis. Several components were considered for the NFD shift parameter in this dissertation: the metric/unit, magnitude, and the algorithm to place the shift to examine the effect of these components on the type-I error rate (alpha) under the null hypothesis of no treatment effect. For the metric factor, four different metric units were considered: constant STD1, constant RSD1, STDk, RSDk; for the magnitude factor, different values of shift parameter f were considered to investigate which f value is the appropriate shift parameter to control the type-I error rate to the nominal level; for the algorithm to implement the delta shift, three different methods were proposed: sequential, non-sequential and single adjustment method. Extensive simulations were conducted to investigate the type-I error rate. Correctness and robustness of the results were examined.
Subject
(authority = RUETD)
Topic
Statistics and Biostatistics
Subject
(authority = ETD-LCSH)
Topic
Sensitivity theory (Mathematics)
Subject
(authority = ETD-LCSH)
Topic
Missing observations (Statistics)
Subject
(authority = ETD-LCSH)
Topic
Clinical trials
RelatedItem
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Title
Rutgers University Electronic Theses and Dissertations
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ETD
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ETD_6200
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (xii, 130 p. : ill.)
Note
(type = degree)
Ph.D.
Note
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Includes bibliographical references
Note
(type = statement of responsibility)
by Lixian Peng
RelatedItem
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TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3514138
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Peng
GivenName
Lixian
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2015-03-02 15:32:58
AssociatedEntity
Name
Lixian Peng
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
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.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ETD
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windows xp
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