|
Showing 1 - 6 of
6 matches in All Departments
*Provides an overview of statistical and analytic methodologies in
real-world evidence to generate insights on healthcare, with a
special focus on the pharmaceutical industry *Examines timely
topics of high relevance to industry such as bioethical
considerations, regulatory standards and compliance requirements
*Highlights emerging and current trends, and provides guidelines
for best practices *Illustrates methods through examples and
use-case studies to demonstrate impact *Provides guidance on
software choices and digital applications for successful analytics.
With ever-rising healthcare costs, evidence generation through
Health Economics and Outcomes Research (HEOR) plays an increasingly
important role in decision-making about the allocation of
resources. Accordingly, it is now customary for health technology
assessment and reimbursement agencies to request for HEOR evidence,
in addition to data from clinical trials, to inform decisions about
patient access to new treatment options. While there is a great
deal of literature on HEOR, there is a need for a volume that
presents a coherent and unified review of the major issues that
arise in application, especially from a statistical perspective.
Statistical Topics in Health Economics and Outcomes Research
fulfils that need by presenting an overview of the key analytical
issues and best practice. Special attention is paid to key
assumptions and other salient features of statistical methods
customarily used in the area, and appropriate and relatively
comprehensive references are made to emerging trends. The content
of the book is purposefully designed to be accessible to readers
with basic quantitative backgrounds, while providing an in-depth
coverage of relatively complex statistical issues. The book will
make a very useful reference for researchers in the pharmaceutical
industry, academia, and research institutions involved with HEOR
studies. The targeted readers may include statisticians, data
scientists, epidemiologists, outcomes researchers, health
economists, and healthcare policy and decision-makers.
With ever-rising healthcare costs, evidence generation through
Health Economics and Outcomes Research (HEOR) plays an increasingly
important role in decision-making about the allocation of
resources. Accordingly, it is now customary for health technology
assessment and reimbursement agencies to request for HEOR evidence,
in addition to data from clinical trials, to inform decisions about
patient access to new treatment options. While there is a great
deal of literature on HEOR, there is a need for a volume that
presents a coherent and unified review of the major issues that
arise in application, especially from a statistical perspective.
Statistical Topics in Health Economics and Outcomes Research
fulfils that need by presenting an overview of the key analytical
issues and best practice. Special attention is paid to key
assumptions and other salient features of statistical methods
customarily used in the area, and appropriate and relatively
comprehensive references are made to emerging trends. The content
of the book is purposefully designed to be accessible to readers
with basic quantitative backgrounds, while providing an in-depth
coverage of relatively complex statistical issues. The book will
make a very useful reference for researchers in the pharmaceutical
industry, academia, and research institutions involved with HEOR
studies. The targeted readers may include statisticians, data
scientists, epidemiologists, outcomes researchers, health
economists, and healthcare policy and decision-makers.
Advancing the development, validation, and use of patient-reported
outcome (PRO) measures, Patient-Reported Outcomes: Measurement,
Implementation and Interpretation helps readers develop and enrich
their understanding of PRO methodology, particularly from a
quantitative perspective. Designed for biopharmaceutical
researchers and others in the health sciences community, it
provides an up-to-date volume on conceptual and analytical issues
of PRO measures. The book discusses key concepts relating to the
measurement, implementation, and interpretation of PRO measures. It
covers both introductory and advanced psychometric and
biostatistical methods for constructing and analyzing PRO measures.
The authors include many relevant real-life applications based on
their extensive first-hand experiences in the pharmaceutical
industry. They implement a wealth of simulated datasets to
illustrate concepts and heighten understanding based on practical
scenarios. For readers interested in conducting statistical
analyses of PRO measures and delving more deeply into the analytic
details, most chapters contain SAS code and output that illustrate
the methodology. Along with providing numerous references, the book
highlights current regulatory guidelines.
Advancing the development, validation, and use of patient-reported
outcome (PRO) measures, Patient-Reported Outcomes: Measurement,
Implementation and Interpretation helps readers develop and enrich
their understanding of PRO methodology, particularly from a
quantitative perspective. Designed for biopharmaceutical
researchers and others in the health sciences community, it
provides an up-to-date volume on conceptual and analytical issues
of PRO measures. The book discusses key concepts relating to the
measurement, implementation, and interpretation of PRO measures. It
covers both introductory and advanced psychometric and
biostatistical methods for constructing and analyzing PRO measures.
The authors include many relevant real-life applications based on
their extensive first-hand experiences in the pharmaceutical
industry. They implement a wealth of simulated datasets to
illustrate concepts and heighten understanding based on practical
scenarios. For readers interested in conducting statistical
analyses of PRO measures and delving more deeply into the analytic
details, most chapters contain SAS code and output that illustrate
the methodology. Along with providing numerous references, the book
highlights current regulatory guidelines.
Statistical evaluation of diagnostic performance in general and
Receiver Operating Characteristic (ROC) analysis in particular are
important for assessing the performance of medical tests and
statistical classifiers, as well as for evaluating predictive
models or algorithms. This book presents innovative approaches in
ROC analysis, which are relevant to a wide variety of applications,
including medical imaging, cancer research, epidemiology, and
bioinformatics. Statistical Evaluation of Diagnostic Performance:
Topics in ROC Analysis covers areas including
monotone-transformation techniques in parametric ROC analysis, ROC
methods for combined and pooled biomarkers, Bayesian hierarchical
transformation models, sequential designs and inferences in the ROC
setting, predictive modeling, multireader ROC analysis, and
free-response ROC (FROC) methodology. The book is suitable for
graduate-level students and researchers in statistics,
biostatistics, epidemiology, public health, biomedical engineering,
radiology, medical imaging, biomedical informatics, and other
closely related fields. Additionally, clinical researchers and
practicing statisticians in academia, industry, and government
could benefit from the presentation of such important and yet
frequently overlooked topics.
|
You may like...
Barbie
Margot Robbie, Ryan Gosling, …
DVD
R194
Discovery Miles 1 940
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
|