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This book begins with an introduction of pragmatic cluster
randomized trials (PCTs) and reviews various pragmatic issues that
need to be addressed by statisticians at the design stage. It
discusses the advantages and disadvantages of each type of PCT, and
provides sample size formulas, sensitivity analyses, and examples
for sample size calculation. The generalized estimating equation
(GEE) method will be employed to derive sample size formulas for
various types of outcomes from the exponential family, including
continuous, binary, and count variables. Experimental designs that
have been frequently employed in PCTs will be discussed, including
cluster randomized designs, matched-pair cluster randomized design,
stratified cluster randomized design, stepped-wedge cluster
randomized design, longitudinal cluster randomized design, and
crossover cluster randomized design. It demonstrates that the GEE
approach is flexible to accommodate pragmatic issues such as
hierarchical correlation structures, different missing data
patterns, randomly varying cluster sizes, etc. It has been reported
that the GEE approach leads to under-estimated variance with
limited numbers of clusters. The remedy for this limitation is
investigated for the design of PCTs. This book can assist
practitioners in the design of PCTs by providing a description of
the advantages and disadvantages of various PCTs and sample size
formulas that address various pragmatic issues, facilitating the
proper implementation of PCTs to improve health care. It can also
serve as a textbook for biostatistics students at the graduate
level to enhance their knowledge or skill in clinical trial design.
Key Features: Discuss the advantages and disadvantages of each type
of PCTs, and provide sample size formulas, sensitivity analyses,
and examples. Address an unmet need for guidance books on sample
size calculations for PCTs; A wide variety of experimental designs
adopted by PCTs are covered; The sample size solutions can be
readily implemented due to the accommodation of common pragmatic
issues encountered in real-world practice; Useful to both academic
and industrial biostatisticians involved in clinical trial design;
Can be used as a textbook for graduate students majoring in
statistics and biostatistics.
Accurate sample size calculation ensures that clinical studies have
adequate power to detect clinically meaningful effects. This
results in the efficient use of resources and avoids exposing a
disproportionate number of patients to experimental treatments
caused by an overpowered study. Sample Size Calculations for
Clustered and Longitudinal Outcomes in Clinical Research explains
how to determine sample size for studies with correlated outcomes,
which are widely implemented in medical, epidemiological, and
behavioral studies. The book focuses on issues specific to the two
types of correlated outcomes: longitudinal and clustered. For
clustered studies, the authors provide sample size formulas that
accommodate variable cluster sizes and within-cluster correlation.
For longitudinal studies, they present sample size formulas to
account for within-subject correlation among repeated measurements
and various missing data patterns. For multiple levels of
clustering, the level at which to perform randomization actually
becomes a design parameter. The authors show how this can greatly
impact trial administration, analysis, and sample size requirement.
Addressing the overarching theme of sample size determination for
correlated outcomes, this book provides a useful resource for
biostatisticians, clinical investigators, epidemiologists, and
social scientists whose research involves trials with correlated
outcomes. Each chapter is self-contained so readers can explore
topics relevant to their research projects without having to refer
to other chapters.
Digital fringe projection (DFP) techniques are used for non-contact
shape measurement of 3D images. In the rapidly expanding field of
3D high-speed imaging, the demand for DFP continues to grow due to
the technology's fast speed, flexibility, low cost, and high
accuracy. High-Speed 3D Imaging with Digital Fringe Projection
Techniques discusses the generation of digital fringe with digital
video projection devices, covering a variety of core technical
aspects. The book begins by establishing the theoretical
foundations of fringe pattern analysis, reviewing various 3D
imaging techniques while highlighting the advantages of DFP. The
author then: Describes the differences between digital light
processing (DLP), liquid crystal display (LCD), and liquid crystal
on silicon (LCoS) Explains how to unwrap phase maps temporally and
spatially Shows how to generate fringe patterns with video
projectors Demonstrates how to convert phase to coordinates through
system calibrations Provides a detailed example of a
built-from-scratch 3D imaging system Incorporating valuable
insights gained during the author's 15+ years of 3D imaging
research, High-Speed 3D Imaging with Digital Fringe Projection
Techniques illuminates the pathway to advancement in high-speed 3D
optical imaging using DFP.
Accurate sample size calculation ensures that clinical studies have
adequate power to detect clinically meaningful effects. This
results in the efficient use of resources and avoids exposing a
disproportionate number of patients to experimental treatments
caused by an overpowered study. Sample Size Calculations for
Clustered and Longitudinal Outcomes in Clinical Research explains
how to determine sample size for studies with correlated outcomes,
which are widely implemented in medical, epidemiological, and
behavioral studies. The book focuses on issues specific to the two
types of correlated outcomes: longitudinal and clustered. For
clustered studies, the authors provide sample size formulas that
accommodate variable cluster sizes and within-cluster correlation.
For longitudinal studies, they present sample size formulas to
account for within-subject correlation among repeated measurements
and various missing data patterns. For multiple levels of
clustering, the level at which to perform randomization actually
becomes a design parameter. The authors show how this can greatly
impact trial administration, analysis, and sample size requirement.
Addressing the overarching theme of sample size determination for
correlated outcomes, this book provides a useful resource for
biostatisticians, clinical investigators, epidemiologists, and
social scientists whose research involves trials with correlated
outcomes. Each chapter is self-contained so readers can explore
topics relevant to their research projects without having to refer
to other chapters.
With the ongoing release of 3D movies and the emergence of 3D
TVs, 3D imaging technologies have penetrated our daily lives. Yet
choosing from the numerous 3D vision methods available can be
frustrating for scientists and engineers, especially without a
comprehensive resource to consult. Filling this gap, Handbook of 3D
Machine Vision: Optical Metrology and Imaging gives an extensive,
in-depth look at the most popular 3D imaging techniques. It focuses
on noninvasive, noncontact optical methods (optical metrology and
imaging).
The handbook begins with the well-studied method of stereo
vision and explains how random speckle patterns or space-time
varying patterns substantially improve the results of stereo
vision. It then discusses stereo particle image velocimetry as a
major experimental means in fluid dynamics, the robust and
easy-to-implement structured-light technique for computer science
applications, digital holography for performing micro- to nanoscale
measurements, and grating, interferometry, and fringe projection
techniques for precisely measuring dynamically deformable natural
objects.
The book goes on to describe techniques that do not require
triangulation to recover a 3D shape, including time-of-flight
techniques and uniaxial 3D shape measurement, as well as 3D
measurement techniques that are not restricted to surface capture,
such as 3D ultrasound, optical coherence tomography, and 3D
endoscopy. The book also explores how novel 3D imaging techniques
are being applied in the promising field of biometrics which may
prove essential to security and public safety.
Written by key players in the field and inventors of important
imaging technologies, this authoritative, state-of-the-art handbook
helps you understand the core of 3D imaging technology and choose
the proper 3D imaging technique for your needs. For each technique,
the book provides its mathematical foundations, summarizes its
successful applications, and discusses its limitations. "
With the ongoing release of 3D movies and the emergence of 3D TVs,
3D imaging technologies have penetrated our daily lives. Yet
choosing from the numerous 3D vision methods available can be
frustrating for scientists and engineers, especially without a
comprehensive resource to consult. Filling this gap, Handbook of 3D
Machine Vision: Optical Metrology and Imaging gives an extensive,
in-depth look at the most popular 3D imaging techniques. It focuses
on noninvasive, noncontact optical methods (optical metrology and
imaging). The handbook begins with the well-studied method of
stereo vision and explains how random speckle patterns or
space-time varying patterns substantially improve the results of
stereo vision. It then discusses stereo particle image velocimetry
as a major experimental means in fluid dynamics, the robust and
easy-to-implement structured-light technique for computer science
applications, digital holography for performing micro- to nanoscale
measurements, and grating, interferometry, and fringe projection
techniques for precisely measuring dynamically deformable natural
objects. The book goes on to describe techniques that do not
require triangulation to recover a 3D shape, including
time-of-flight techniques and uniaxial 3D shape measurement, as
well as 3D measurement techniques that are not restricted to
surface capture, such as 3D ultrasound, optical coherence
tomography, and 3D endoscopy. The book also explores how novel 3D
imaging techniques are being applied in the promising field of
biometrics-which may prove essential to security and public safety.
Written by key players in the field and inventors of important
imaging technologies, this authoritative, state-of-the-art handbook
helps you understand the core of 3D imaging technology and choose
the proper 3D imaging technique for your needs. For each technique,
the book provides its mathematical foundations, summarizes its
successful applications, and discusses its limitations.
Digital fringe projection (DFP) techniques are used for non-contact
shape measurement of 3D images. In the rapidly expanding field of
3D high-speed imaging, the demand for DFP continues to grow due to
the technology's fast speed, flexibility, low cost, and high
accuracy. High-Speed 3D Imaging with Digital Fringe Projection
Techniques discusses the generation of digital fringe with digital
video projection devices, covering a variety of core technical
aspects. The book begins by establishing the theoretical
foundations of fringe pattern analysis, reviewing various 3D
imaging techniques while highlighting the advantages of DFP. The
author then: Describes the differences between digital light
processing (DLP), liquid crystal display (LCD), and liquid crystal
on silicon (LCoS) Explains how to unwrap phase maps temporally and
spatially Shows how to generate fringe patterns with video
projectors Demonstrates how to convert phase to coordinates through
system calibrations Provides a detailed example of a
built-from-scratch 3D imaging system Incorporating valuable
insights gained during the author's 15+ years of 3D imaging
research, High-Speed 3D Imaging with Digital Fringe Projection
Techniques illuminates the pathway to advancement in high-speed 3D
optical imaging using DFP.
This book systematically introduces the clinical and imaging
characteristics of mediastinal diseases, with emphasis on the
essential relationship between clinical diseases and imaging, and
on imaging diagnosis and differential diagnosis. This book
systematically expounds the etiology, clinical and imaging
manifestations, diagnosis, differential diagnosis and treatment of
diseases, supplemented by a large number of cases to focus on
analysis, focus on clinical thinking, and strive to combine theory
with practice, so that readers have a systematic and in-depth
understanding of diagnosis and treatment and differential diagnosis
of related diseases.
Variational inequalities (VIs) arise from a wide range of
application areas, like mechanics, control theory, engineering, and
finance. One of the emerging applications of variational
inequalities in finance is valuation of American-style options. An
option is a derivative contract where the future payoffs to the
buyer and seller of the contract are determined by the price of
another security, such as a common stock or a basket of stocks.
American option pricing can be formulated as an obstacle problem, a
particular example of VIs. To solve time dependent variational
inequalities numerically, we employ the explicit or implicit Euler
method for time-discretization and the finite element method (FEM)
for space-discretization with adaptive time-space mesh refinement
techniques. Adaptive mesh refinement is an important tool to deal
with multiscale phenomena and to reduce the size of the linear
systems that arise from the discretization.
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