Foreword
Page: i-iii (3)
Author: Vedprakash Mishra
DOI: 10.2174/9789815123791123010001
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Preface
Page: iv-v (2)
Author: Satyawan Singh Patel
DOI: 10.2174/9789815123791123010002
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Acknowledgements
Page: vi-vi (1)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010003
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Study Designs in Clinical Research
Page: 1-13 (13)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010004
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Abstract
Study designs in medical research fall mainly into three categories:
Observational studies, Interventional studies & meta-analyses. Further, each type of
study comprises of subtypes. Each study design with its subtypes, and applicability of a
specific study design, along with advantages & limitations, are discussed in this
chapter.
Scales of Measurement, Descriptive Statistics & Data Presentation
Page: 14-30 (17)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010005
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Abstract
The scales of measurement could be numerical, nominal or ordinal. The
measurement of data requires measurement of its central tendency and discussion. Such
data can be presented, depending on its type & nature, in the form of tables & figures.
The different types of descriptive statistics & the suitable form of presentation are
discussed in this chapter.
Inferential Statistics
Page: 31-54 (24)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010006
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Abstract
Probability could be objective or subjective. Byestherom is a formula to
calculate conditional Probability. The sample methods of random sampling are simple
random sampling, systematic random sampling, Stratified random sampling, and
cluster random sampling. Use of hypothesis testing, if used as inferential statistics,
definite steps are required to be followed. Using confidence intervals as inferential
statistics provide more useful information in clinical research. This chapter
incorporates a discussion on these aspects.
Statistical Methods for Relationship Variables
Page: 55-70 (16)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010007
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Abstract
In the language of statistics, research is a planned & systemic method of data
collection, analysis, & drawing conclusions. In this chapter, a demonstration of the
relationship between numerical, nominal & ordinal data & calculation of other
statistical techniques applicable in critical research, is described in a nutshell.
Clinical Research
Page: 71-88 (18)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010008
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Abstract
The clinical trial could either be an Explanatory Trial/ Randomised Control
Trial (RCT) or Correlational Trial/ Pragmatic Trial. For developing new molecules as a
drug, RCTs require human studies conducted in 4 phases called Phase I to phase IV of
clinical trials. Pragmatic Trials are Correlational Trials. As such RCT & Pragmatic
Trials are not dichotomous, there is a continuum. A PRECIS has been developed to
assess the said trials. The reverse pharmacology approach is recommended to generate
scientific evidence to make herbal drugs more efficacious & safe. These aspects are
elaborated on in this chapter.
Survey Research
Page: 89-98 (10)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010009
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Abstract
A survey is one of the most common methods in health sciences research.
As in this case, choosing a suitable study design depends on the research question, so
also survey research questions also decide methods. The decision of application of
scale of measurement depends on the nature of the observations, which could be
numerical, nominal, or ordinal. If research develops his/her new survey instrument
(survey questionnaire), its validity & reliability requires other important treatments.
This forms the subject of discussion in this chapter.
Planning and Writing Research Projects
Page: 99-107 (9)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010010
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Abstract
Reading research papers/literature should be done through reviewing. It
should not be not skimming. Biases in a study seriously affect the conclusion of the
study adversely. While writing research reports, discrepancies in text, tables, and
figures may reflect after-thought data treatment by the researchers: these and other
aspects during the planning of research projects and report writing. Precautions
required are the very purpose of this chapter.
APPENDIX-A
Page: 108-114 (7)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010011
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Glossary
Page: 115-126 (12)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010012
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References
Page: 127-128 (2)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010013
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Subject Index
Page: 129-133 (5)
Author: S.S. Patel and Aditya Patel
DOI: 10.2174/9789815123791123010014
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Introduction
Elements Of Clinical Study Design, Biostatistics & Research is designed as a toolbox for biomedical researchers. The book's primary focus is on applications in clinical research, and will benefit students and researchers involved in the biomedical field. This book addresses the problems that many practitioners experience in choosing and implementing fit-for-purpose data analysis methods to answer critical inferential questions for binomial and count data. The book is written in simple language avoiding complex derivations and mathematical formulae allowing it to explain the most basic concepts of research methodology. Making good use of numerous tables, graphs and tips, this book demystifies the process for readers. 7 structured Chapters take the reader through the entire research process: choosing a question, designing a study, collecting the data, using univariate, bivariate, and multivariable analysis, and publishing the results. Each chapter discusses the strengths and weaknesses of the methods and suggests practical recommendations. An appendix on ethical research guidelines, along with a glossary and reference list comprehensively round up the book contents. It gives students and practitioners a multidisciplinary understanding of the concepts and techniques involved in designing, monitoring, and analyzing various types of studies. The book's balanced set of homework assignments and in-class exercises are appropriate for students and researchers in the areas of biostatistics, epidemiology, medicine, pharmacy, and public health.