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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.
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.
One of the largest political protests in contemporary Korean
history, the May 1980 Kwangju Uprising still exerts a profound,
often contested, influence in Korean society. Through a deft
combination of personal reflections and academic analysis,
Contentious Kwangju offers a comprehensive examination of the
multiple, shifting meanings of this seminal event and explains how
the memory of Kwangju has affected Korean life from politics to
culture. The first half of the book offers highly personal
perspectives on the details of the uprising itself, including the
Citizens' Army, the fleeting days of Kwangju citizen autonomy, the
activities of American missionaries, and the aftermath following
the uprising's suppression by government forces. The second half
provides a wide-ranging scholarly assessment of the impact of
Kwangju in South Korea, from democratization and the fate of
survivors to regional identity and popular culture, concluding with
an examination of Kwangju's significance in the larger flow of
modern Korean history. In keeping with the book's title, the essays
offer competing interpretations of the Kwangju Uprising, yet
together provide the most thorough English-language treatment to
date of the multifaceted, sweeping significance of this pivotal
event.
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