Describing and explaining social phenomena is a complex task. Box’s quote speaks to the point that it is a near-impossible undertaking to fully explain such systems—physical or social—using a set of models. Yet even though these models contain some error, the models nevertheless assist with illuminating how the world works and advancing social change.

The competent quantitative researcher understands the balance between making statements related to theoretical understanding of relationships and recognizing that our social systems are of such complexity that we will always have some error. The key, for the rigorous researcher, is recognizing and mitigating the error as much as possible.

As a graduate student and consumer of research, you must recognize the error that might be present within your research and the research of others.

• As you read the article, reflect on George Box’s quote in the introduction for this Discussion.
• For additional support, review the Skill Builder: Independent and Dependent Variables, which you can find by navigating back to your Blackboard Course Home Page. From there, locate the Skill Builder link in the left navigation pane.

Post a very brief description (1–3 sentences) of the article you found and address the following:

1. Describe how you think the research in the article is useful (e.g., what population is it helping? What problem is it solving?).
2. Using Y=f(X) +E notation, identify the independent and dependent variables.
3. How might the research models presented be wrong? What types of error might be present in the reported research?

Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.

References

Dietz, T., & Kalof, L. (2009). Introduction to social statistics: The logic of statistical reasoning. 1-63. Retrieved from https://class.waldenu.edu/bbcswebdav/institution/USW1/201870_27/XX_RSCH/RSCH_8210/readings/USW1_RSCH_8210_Week01_DietzKalof_chapter01

 Kariman, H., Vajihi, F., Amini, A., Shahrami, A., Arhami-Dolatabadi, A., Shojaee, M., & Baratloo, A. (2017). Hyoscine versus diazepam for the management of true vertigo in the emergency department. Bangladesh Journal of Pharmacology, 12(2), 95–100. https://doi-org.ezp.waldenulibrary.org/10.3329/bjp.v12i2.29962 

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Short Book Reviews
Editor: Simo Puntanen

Linear Model Methodology
André I. Khuri
Chapman & Hall/CRC, 2010, xix + 542 pages, £ 63.99 / US$ 99.95, hardcover
ISBN: 978-1-58488-481-1

Table of contents

1. Linear models: some historical perspectives 8. Balanced linear models
2. Basic elements of linear algebra 9. The adequacy of Satterthwaite’s approximation
3. Basic concepts in matrix algebra 10. Unbalanced fixed-effects models
4. The multivariate normal distribution 11. Unbalanced random and mixed models
5. Quadratic forms in normal variables 12. Additional topics in linear models
6. Full rank linear models 13. Generalized linear models
7. Less-than-full-rank linear models

Readership: All readers interested in regression presented with a mix of theory and practice.

The material on which this book is based has been taught in a couple of courses at the University
of Florida for about 20 years and the author’s skills and experience in doing this are superbly
represented in this fine text. The presentation itself leans more toward the theoretical aspects,
but there are numerous exercises that reinforce both the theoretical and the practical aspects of
regression. (However, no solutions are provided.) “Chapters 11 and 12 can be particularly helpful
to graduate students looking for dissertation topics.” (Preface) This is an excellent, reliable, and
comprehensive text.

Norman R. Draper: draper@stat.wisc.edu
Department of Statistics, University of Wisconsin – Madison

1300 University Avenue, Madison, WI 53706-1532, USA

Knowledge Discovery for Counterterrorism and Law Enforcement
David Skillicorn
Chapman & Hall/CRC, 2008, xx + 330 pages, £ 49.99 / US$ 79.95, hardcover
ISBN: 978-1-4200-7399-7

Table of contents

1. Introduction 6. Looking inside groups – relationship discovery
2. Data 7. Discovery from public textual data
3. High-level principles 8. Discovery in private communication
4. Looking for risk – prediction and anomaly detection 9. Discovering mental and emotional state
5. Looking for similarity – clustering 10. The bottom line

Readership: Anyone first venturing into knowledge discovery for counterterrorism.

C© 2010 The Authors. Journal compilation C© 2010 International Statistical Institute. Published by Blackwell Publishing Ltd, 9600 Garsington Road,
Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

SHORT BOOK REVIEWS 317

This is a discursive book, outlining all sorts of methods, which might be used in counterterrorism,
and speculating on how they might be employed. There are very few real applied examples
and these are only described in brief. I suppose this should not surprise us for this area
of application, but it detracts from the text’s interest. There is a whole 30-page chapter on
cluster analysis, which has just one artificial example of three people and their height and
age. Even if no counterterrorism examples can be used, surely something more stimulating
could have been found. The standard result on the large number of false positives that arise in
searching information for terrorists properly appears, though the calculation itself is not given
(and strangely enough Bayes’ Theorem does not appear at all). The author’s comment on the
result is worth quoting in full: “. . . the ACM committee assume that 99.999% accuracies are
unattainably remote, despite the fact that defect rates well below this are commonplace in many
industrial settings, not by some kind of magic but by working at the process to reduce defects.”
As a statistician, this kind of positive thinking leaves me very skeptical.

Antony Unwin: unwin@math.uni-augsburg.de
Universität Augsburg, Institut für Mathematik

D-86135 Augsburg, Germany

Statistical Methods for Categorical Data Analysis, Second Edition
Daniel A. Powers, Yu Xie
Emerald Group, 2008, xvii + 317 pages, £ 39.99 / US$ 69.95, hardcover
ISBN: 978-0-1237-2562-2

Table of contents

1. Introduction 6. Statistical models for event occurrence
2. Review of linear regression models 7. Models for ordinal dependent variables
3. Models for binary data 8. Models for nominal dependent variables
4. Loglinear models for contingency tables A. The matrix approach to regression
5. Multilevel models for binary data B. Maximum likelihood estimation

Readership: Social science researchers.

There are quite a few books on analyzing categorical data. This one has the expressed aim
of integrating the transformational approach familiar to statisticians with the latent variable
approach “often taken by economists.” It covers a fairly wide range of models in a reasonably
successful manner. Though it has a certain amount of mathematics, this is not covered in any
great depth. Linear regression is explained in matrix form in an appendix and the Bayes factor is
described as “complicated and beyond the scope of this book.” In keeping with the other books
in this area, there are disappointingly few graphics and mosaic plots that do not get a mention.
In contrast with some of the other books, there are not many motivating examples and when
the examples included are analyzed the results are not discussed in any detail. If they had been
(or if graphics had been used) the authors might have noticed the two errors in Table 6.8 on
page 191 that I spotted. Although there are no exercises, there is a supporting website, which
includes code for the examples using a variety of software packages. The book is now in its
second edition, so it has already achieved a certain amount of recognition. With better examples
it could get more.

Antony Unwin: unwin@math.uni-augsburg.de
Universität Augsburg, Institut für Mathematik
D-86135 Augsburg, Germany

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From Finite Sample to Asymptotic Methods in Statistics
Pranab K. Sen, Julio M. Singer, Antonio C. Pedroso de Lima
Cambridge University Press, 2009, xii + 386 pages, £ 45.00 / US$ 70.00, hardcover
ISBN: 978-0-521-87722-0

Table of contents

1. Motivation and basic tools 7. Asymptotic distributions
2. Estimation theory 8. Asymptotic behavior of estimators and tests
3. Hypothesis testing 9. Categorical data models
4. Elements of statistical decision theory 10. Regression models
5. Stochastic processes: an overview 11. Weak convergence and Gaussian processes
6. Stochastic convergence and probability inequalities

Readership: Advanced undergraduate or beginning graduate students in statistics, biostatistics,
or applied statistics, academic researchers in statistically oriented fields.

The authors point out in the preface that “. . . , our intent is to provide a broad view of finite-
sample statistical methods, to examine their merits and caveats, and to judge how far asymptotic
results eliminate some of the detected impasses, providing the basis for sound application of
approximate statistical inference in large samples.” The book succeeds admirably in its aim of
providing an overview of finite-sample (exact or small) methods, appraising their scope and
integrating them to asymptotic (approximate or large-sample) inference. The treatment of the
material is application-oriented and yet mathematically rigorous.

In Chapter 1 the authors motivate their approach through a set of illustrative examples ranging
from very simple to more complex applications. Also a summary of some basic tools and results
(on matrix algebra, real analysis, probability distributions, order statistics, and quantiles) needed
in the text is provided. Chapters 2 and 3 lay out the two building blocks of statistical inference,
estimation and testing, and in these chapters the authors address the important issues relating
to likelihood, sufficiency and invariance, among others. The chapter titles shown above indicate
the range of topics covered in the text.

The book is very well written and clear. The overall standard of explanation is very good,
new ideas are accompanied by several worked examples, although one might have wished also
numerical examples with some indication of how the theory performs in practice. There are
also a large number of suitable exercises for the reader. In my view, this text can be warmly
recommended for lecture courses in asymptotic statistics and courses in statistical inference.

Erkki P. Liski: erkki.liski@uta.fi
Department of Mathematics and Statistics
FI-33014 University of Tampere, Finland

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Steps Towards a Unified Basis for Scientific Models and Methods
Inge S. Helland
World Scientific, 2010, xviii + 257 pages, £ 56.00 / US$ 75.00, hardcover
ISBN: 978-981-4280-85-3

Table of contents

1. The basic elements 8. Multivariate data analysis and statistics
2. Statistical theory and practice 9. Quantum mechanics and the diversity of concepts
3. Statistical inference under symmetry 10. Epilogue
4. The transition from statistics to quantum theory A.1. Mathematical aspects of basic statistics
5. Quantum mechanics from a statistical basis A.2. Transformation groups and group transformations
6. Further development of quantum mechanics A.3. Technical aspects of quantum mechanics
7. Decisions in statistics A.4. Some aspects of partial least squares regression

Readership: Those interested in the broader aspects of statistical theory and concepts and
especially those with a concern with links to quantum theory.

This wide-ranging book aims to address and link broad conceptual issues, in particular in
statistical theory and quantum theory. The introductory chapter discusses complementarity in a
wide sense and introduces the notion of conceptually defined variables, c-variables. These link
with counterfactual variables and latent variables in the sense used in statistical theory, but are
intended to be broader. There follows a remarkably clear and compact summary of the theory
of statistical inference, limited mainly by a concentration on transformation models. Remarks
on a range of more applied issues make an interesting commentary on the more mathematical
parts. Chapters 5 and 6 deal with quantum mechanics, starting with a summary account of the
conventional approach and then leading to a development from a new set of axioms claimed
to have a clearer intuitive content, an aspect which the author considers important. The final
Chapters cover a wide range of topics, mostly statistical. The writing is lucid. Whether a useful
synthesis has been achieved is unclear to this reviewer.

David Cox: david.cox@nuffield.ox.ac.uk
Nuffield College, New Road

Oxford, OX1 1NF, UK

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A First Course in Probability and Statistics
B. L. S. Prakasa Rao
World Scientific, 2008, xii + 317 pages, £ 26.00 / US$ 48.00, softcover (also available as hard-
cover)
ISBN: 978-981-283-654-0

Table of contents

1. Why statistics? 8. Estimation
2. Probability on discrete sample spaces 9. Interval estimation and testing of hypotheses
3. Discrete probability distributions 10. Linear regression and correlation
4. Continuous probability distributions Appendix A. References
5. Multivariate probability distributions Appendix B. Answers to selected exercises
6. Functions of random vectors Appendix C. Tables
7. Approximations to some probability distributions

Readership: Undergraduate courses in statistics and probability, mathematics students who are
studying probability.

This book assumes that the reader has completed a course on calculus and has a thorough
knowledge and understanding of this. The approach is very mathematical, with many proofs
included. The text while advertised for those doing Social Science and Business Administration
may find the title misleading as it is certainly suitable for those studying mathematics and
statistics but maybe be difficult for the other subject disciplines.

The book is very comprehensive in its coverage of the topics included and contains a wealth
of exercises at the end of each chapter. Solutions to only a selected few of these exercises can be
found in the appendix and there are no solutions for Chapters 8–10. For a first course it would
have been useful to include more solutions such as question 10.1 asks the reader to determine
the regression line that best fits five given points.

This is a book that is intended for those of a mathematical mind, who have a background in
calculus, and a good grasp of mathematics in general.

Susan Starkings: starkisa@lsbu.ac.uk
Centre for Learning Support and Development, London South Bank University

103 Borough Road, London, SE1 0AA, UK

Statistics for Engineers: An Introduction
S. J. Morrison
Wiley, 2009, xiv + 177 pages, € 46.00 / £ 39.95 / US$ 70.00, hardcover
ISBN: 978-0-470-74556-4

Table of contents

1. Nature of variability 8. Conclusion
2. Basic statistical methods Appendix A: Guidelines
3. Production Appendix B: Recommended books
4. Engineering design Appendix C: Periodicals
5. Research and development Appendix D: Supplementary bibliography
6. Background Appendix E: Statistical tables
7. Quality management

Readership: Students on or considering courses in engineering.

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This book is written by an engineer for an engineering readership and contains practical advice
and guidance on the statistical results obtained in a variety of situations. A broad range of
statistical methods that is relevant to engineering with the minimum of mathematics and
maximum of explanation is the essence of this text.

The book is very comprehensive in its coverage of the engineering topics and fully explains
the techniques used here. The text focuses on the statistical methods that engineers need, how
they work and how to use them safely. Also included is a wealth of relevant references at the
end of each chapter as well as those in the appendices. There are no exercises for the reader
to attempt as it is assumed that the lecturer will provide these but it is extremely useful for
explanations.

This is a book that is intended for engineering students and is to be recommended to have in
any college or university that has students studying this subject discipline.

Susan Starkings: starkisa@lsbu.ac.uk
Centre for Learning Support and Development, London South Bank University
103 Borough Road, London, SE1 0AA, UK

Exploring the Origin, Extent, and Future of Life: Philosophical, Ethical and
Theological Perspectives
Constance M. Bertka (Editor)
Cambridge University Press, 2009, xii + 324 pages, £ 65.00 / US$ 120.00, hardcover
ISBN: 978-0-521-86363-6

Table of contents

1. Astrobiology in societal context (Constance M. Bertka) 9. A historical perspective on the extent and search for life
Part I. Origin of Life (Steven J. Dick)

2. Emergence and the experimental pursuit of the origin of 10. The search for extraterrestrial life: epistemology, ethics,
life (Robert M. Hazen) and worldviews (Mark Lupisella)

3. From Aristotle to Darwin, to Freeman Dyson: changing 11. The implications of discovering extraterrestrial life:
definitions of life viewed in historical context (James different searches, different issues (Margaret S. Race)
E. Strick) 12. God, evolution, and astrobiology (Cynthia S.W. Crysdale)

4. Philosophical aspects of the origin-of-life problem: the Part III. Future of Life
emergence of life and the nature of science (Iris Fry) 13. Planetary ecosynthesis on Mars: restoration ecology and

5. The origin of terrestrial life: a Christian perspective environmental ethics (Christopher P. McKay)
(Ernan McMullin) 14. The trouble with intrinsic value: an ethical primer for

6. The alpha and the omega: reflections on the origin and astrobiology (Kelly C. Smith)
future of life from the perspective of Christian theology 15. God’s preferential option for life: a Christian perspective
and ethics (Celia Deane-Drummond) on astrobiology (Richard O. Randolph)

Part II. Extent of Life 16. Comparing stories about the origin, extent, and future of
7. A biologist’s guide to the Solar System (Lynn J. life: an Asian religious perspective (Francisca Cho)

Rothschild)
8. The quest for habitable worlds and life beyond the Solar

System (Carl Pilcher, Jack J. Lissauer)

Readership: Readers interested in Astrobiology.

I was intrigued with the title to see how statistics was to be used in a book of this title and
indeed why it was sent to the ISI for a review. The book is divided into three parts namely (i)
Origin of life, (ii) Extent of life, and (iii) Future of life. The text contains very little statistics;
however, those that are present show an interesting use of statistics. I would not suggest that this
is a statistics book in any way, shape or form just that it has some, albeit very little, statistics
contained within its pages. So unless one is interested in the area of astrobiology, religion, and
ethics or has a philosophical interest then this is not one for you. Having said that I found the

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322 SHORT BOOK REVIEWS

book to be very interesting and refreshingly different form the usual academic books that comes
my way.

The book was completed with support from the National Aeronautics and Space Administra-
tion and the John Temple Foundation. It is a valuable text for graduate students and researchers
with an interest in astrobiology.

Susan Starkings: starkisa@lsbu.ac.uk
Centre for Learning Support and Development, London South Bank University
103 Borough Road, London, SE1 0AA, UK

Philosophical Transactions of The Royal Society A, 367 (1906)
Theme Issue ‘Statistical Challenges of High-dimensional Data’
David L. Banks, Peter J. Bickel, Iain M. Johnstone, D. Michael Titterington (Editors)
Royal Society Publishing, 2009, 236 pages, £ 58.00, softcover
ISBN: 978-0-85403-779-7

Table of contents

Introduction (I.M. Johnstone, D.M. Titterington) Statistical inference for exploratory data analysis and model
Selective inference in complex research (Y. Benjamini, diagnostics (A. Buja, D. Cook, H. Hofmann, M. Lawrence,

R. Heller, D. Yekutieli) E.-K. Lee, D.F. Swayne, H. Wickham)
Observed universality of phase transitions in high- Sufficient dimension reduction and prediction in regression

dimensional geometry, with implications for modern data (K.P. Adragni, R.D. Cook)
analysis and signal processing (D. Donoho, J. Tanner) Identifying graph clusters using variational inference and

On landmark selection and sampling in high-dimensional links to covariance parametrization (D. Barber)
data analysis (M.-A. Belabbas, P.J. Wolfe) Classification of sparse high-dimensional vectors (Yu. I.

An overview of recent developments in genomics and Ingster, C. Pouet, A.B. Tsybakov)
associated statistical methods (P.J. Bickel, J.B. Brown, Feature selection by higher criticism thresholding achieves
H. Huang, Q. Li) the optimal phase diagram (D. Donoho, J. Jin)

Cherry-picking for complex data: robust structure discovery
(D.L. Banks, L. House, K. Killourhy)

Readership: A very good book for those who are interested in knowing what is meant by high-
dimensional problems, where they are coming from, and how statisticians and computer and
information scientists are solving them.

The book under review is a collection of 11 excellent articles reprinted from the Philosophical
Transactions of the Royal Society, vol. 367, pages 4235 through 4470. The front cover reminds
us that the Royal Society is the world’s longest running science journal, from the back cover
we learn the Society was founded in 1660. Another great name is associated with these papers,
they were prepared as a part of the program Statistical Theory and Methods for Complex High-
Dimensional Data at the Isaac Newton Institute for Mathematical Sciences in Cambridge, UK.

For anyone working or wishing to work in this area or just learn what is going on in the most
happening part of our subject, this is a wonderful book, providing introduction and overview
of what is now known as well as new emerging ideas, methods, theorems, and conjectures.
Topics covered include variable/feature selection, regression, classification, visual exploration
and novel visual confirmatory analysis, multiple tests, robust structure hunting, graph clusters,
model selection, and sufficient dimension regression. Among all these exciting theoretical
and practical developments, perhaps the most wonderful are the conjectures on and partial
verification of phase transitions in high-dimensional multiple testing by Donoho and Tanner
(pp. 4273–4294), and the partial verification of optimality of Tukey’s Higher Criticism under
phase transition by Donoho and Jin (pp. 4449–4470).

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A brief review of the papers follows. In their introductory as well as survey of high-dimensional
problems, Johnstone and Titterington explain that high dimension means a high-dimensional
parameter, usually but not always accompanied by a relatively small replication. Such problems
defy the old requirement that the number of sampling units should exceed the number of
parameters, more so the better. These problems arise in molecular biology, image processing,
communication, and other diverse areas. These problems are usually solved by a sparsity
assumption that only a small number of many parameters are nonzero. But one does not know
which ones are nonzero, so the problem remains even with the sparsity assumption. It turns out
that the signals, that is, the nonzero parameters should be sufficiently large in magnitude to be
detected. One could describe this as the first stage of the high-dimensional statistics. This stage
still continues but a second stage has begun too. People working in this area have begun to worry
about what happens when the sparsity assumption fails at least partly, that is, there are fewer
signals than what is provided for by assumed levels of sparsity and the signals may be both
rare and weak. Then the methods for high dimensions developed in the first stage breaks down.
Donoho and Tanner, in what is perhaps the most stunning article, show the level of sparsity at
which breakdown begins to show up is surprisingly stable over different examples and domains
and relate this to combinatorial geometry of polytopes. This is very important work still in its
infancy, there will be many beautiful as well as useful results.

Since many of these problems originate in molecular biology, in fact in Genomics specifically,
Bickel et al. provide a very useful survey of old and very new problems in different subareas
of Genomics and the solutions being offered within Classical Statistics, Machine Learning and
Bayesian Analysis.

Buja et al. show how visual display, generally considered part of exploratory analysis, can also
be used for confirmatory analysis like testing of hypotheses, this seems a very novel idea. Banks
et al. discuss robust structure discovery, which is important since robustness of high-dimensional
analysis is rarely studied. Adragni and Cook discuss (sufficient) dimension reduction, which
is somewhat like principal components, but is applied to inverse regression and aims at being
nonparametric. The idea is due to K.C. Li but developed a lot by these authors. Benjamini et
al. provide a lovely introduction to the famous Benjamini–Hochberg multiple test and two very
useful new techniques to cope with selection bias and problems of multiple tests, for example to
discover genes influencing some disease or resistance to it, conducted independently at different
sites.

This is only a sparse picture of a complex high-dimensional landscape that unfolds in these
eleven articles. In the introductory survey of the first article, among other things there is mention
of a “brief encounter with Bayesian Statistics.” If the followers of Reverend Bayes are invited
to contribute to another volume, I am sure the brief encounter would explode into another set
of new concepts like “shotguns,” “horseshoes,” and other quite new and successful principles
for variable selection in very complex problems that do not violate the very strict scientific
standards laid down by Sir Isaac.

Jayanta K. Ghosh: ghosh@stat.purdue.edu
Department of Statistics, Purdue University

West Lafayette, IN 47909, USA

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R Through Excel: A Spreadsheet Interface for Statistics, Data Analysis, and Graphics
Richard M. Heiberger, Erich Neuwirth
Springer, 2009, xxiv + 342 pages, € 54.95 / £ 49.99 / US$ 64.95, softcover
ISBN: 978-1-4419-0051-7

Table of contents

1. Getting started 9. What is least squares?
2. Using RExcel and R Commander 10. Multiple regression – two X -variables
3. Getting data into R 11. Polynomial regression
4. Normal and t distributions 12. Multiple regression – three or more X -variables
5. Normal and t workbook 13. Contingency tables and the chi-square test
6. t-Tests A. Installation of RExcel
7. One-way ANOVA B. Nuisances – installation, startup, or execution
8. Simple linear regression

Readership: Students, researchers, and others who wish to use R but avoid the command line.

This book is essentially a manual for the RExcel software. RExcel is an add-in to Excel which
allows access to the statistical functionality of R including user-contributed packages via the
Excel interface. Although the book contains 342 pages, there is limited text. Most commonly
a page consists of one or more screenshots showing how to use RExcel. The whole book is
reproduced in color, on glossy paper.

Readers are guided through the menu system (which is based on R Commander) to see
how to carry out common statistical procedures. The level of statistical understanding required
is roughly that of an introductory applied statistics subject at university level (t-tests, one-
way ANOVA, multiple regression, contingency tables). A number of workbooks demonstrating
various statistical calculations and procedures come with RExcel. These are intended to support
statistics courses. A workbook titled Demo Files for the book R through Excel is described in
the book. It covers topics such as data formats, normal and t distributions, and linear regression.

Two appendices deal with installation and possible problems.
I found very few errors. Unfortunately, the help system changed with R 2.10, so the help

window shown on p.36 no longer applies. All the author names and dates in the bibliography
are duplicated. The index is rather limited, with no entry for “workbook,” for example, when I
wanted to look that up.

For anyone wishing to learn RExcel this book would be a useful purchase.

David J. Scott: d.scott@auckland.ac.nz
Department of Statistics, The University of Auckland

Private Bag 92019, Auckland 1142, New Zealand

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Machine Learning: An Algorithmic Perspective
Stephen Marsland
Chapman & Hall/CRC, 2009, xvi + 390 pages, £ 38.69 / US$ 62.96, hardcover
ISBN: 978-1-4200-6718-7

Table of contents

1. Introduction 9. Unsupervised learning
2. Linear discriminants 10. Dimensionality reduction
3. The multi-layer perception 11. Optimization and search
4. Radial basis functions and splines 12. Evolutionary learning
5. Support vector machines 13. Reinforcement learning
6. Learning with trees 14. Markov Chain Monte Carlo (MCMC) methods
7. Decision by committee: ensemble learning 15. Graphical models
8. Probability and learning 16. Python

Readership: Undergraduate computer science and engineering students.

This book is intended to be a practical first introduction to the ideas and methods of machine
learning, for those without substantial mathematical machinery to hand. It thus places emphasis
on algorithms, rather than the mathematics behind them, and is liberally illustrated with
many programming examples, using Python. It includes a basic primer on Python and has
an accompanying website.

It has excellent breadth, and is comprehensive in terms of the topics it covers, both in terms
of methods (e.g., including neural networks, support vector machines, ensemble methods, tree
classifiers, reinforcement learning, stochastic methods, tracking, belief networks, etc.) and in
terms of concepts and theory (e.g., dimensionality issues, optimization, etc.).

There is a “further reading” section at the end of each chapter, which is useful, but the
references have not been collected together in a list at the end of the book, which can be a
disadvantage – something to consider for the second edition.

Overall, I think the author has succeeded in his aim: the book provides an accessible
introduction to machine learning. It would be excellent as a first exposure to the subject, and
would put the various ideas in context, before moving on to a more elaborate and deep treatment,
such as that in Hastie, Tibshirani, and Friedman’s The Elements of Statistical Learning.

This book also includes the first occurrence I have seen in print of a reference to a zettabyte of
data (1021 bytes) – a reference to “all the world’s computers” being estimated to contain almost
a zettabyte by 2010.

David J. Hand: d.j.hand@imperial.ac.uk
Mathematics Department, Imperial College

London SW7 2AZ, UK

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Introduction to Social Statistics: The Logic of Statistical Reasoning
Thomas Dietz, Linda Kalof
Wiley-Blackwell, 2009, xxxviii + 569 pages, € 32.20 / £ 27.99 / US$ 94.95, hardcover
ISBN: 978-1-4051-6902-8

Table of contents

1. An introduction to quantitative analysis 10. Using sampling distributions: hypothesis tests
2. Some basic concepts 11. The subtle logic of analysis of variance
3. Displaying data one variable at a time 12. Goodness of fit and models of frequency tables
4. Describing data 13. Bivariate regression and correlation
5. Plotting relationships and conditional distributions 14. Basics of multiple regression
6. Causation and models of causal effects Appendix A. Summary of variables in examples
7. Probability Appendix B. Mathematics review
8. Sampling distributions and inference Appendix C. Statistical tables
9. Using sampling distributions: confidence intervals

Readership: Undergraduate students in the social sciences.

The book opens with the statement that statistics is hard. While I am not sure that that is the
best way to encourage readership and sales, it is certainly a message I endorse, especially for
the intended readership of the book. People who are studying statistics as a necessary sideline
to their real interests often feel discouraged by the effort needed to master it, and reflect this
back on themselves (as in “I am unable to do it”), with the implication that they are inadequate
in some way. Instead it is healthier to take the attitude of this book – that the subject matter is
intrinsically hard, and one should expect to have to work at it.

Unfortunately, to illustrate the hardness of statistics, the authors quote Persi Diaconis
(misspelling his name) saying “Our brains are just not wired to do probability problems very
well.” Diaconis was, as he said, speaking of probability (he was discussing the Monty Hall
problem), and probability and statistics are very different kinds of beast. One is a branch of
mathematics, describing the empirical consequences of given models, and the other is technology
of inferring likely underlying structures from empirical data.

The authors then go on to say “it was not until the 1600s, when Galileo correctly analyzed
chances in games based on dice, that people began to understand the probabilities that underpin
random processes.” It is true that Galileo did investigate such matters, in the early part of the
seventeenth century, but his paper was not published until 1718 and people normally date the
start of a formal understanding of probability to the correspondence between Pascal and Fermat
in 1654, again about a gambling problem.

The book criticizes the cookbook approach to statistics. This is a criticism with which I agree
entirely. However, I think the authors have not moved as far from this approach as they could.
One illustration is provided by Chapter 4, which essentially lists various simple descriptive
statistics, with very little comparative evaluation. In fact the appropriate statistic to use (e.g.,
mean or median) depends on the question one is trying to answer, and that fact can be used to
develop statistical ideas and tools from a clearly noncookbook orientation.

I liked the description of quantitative data analysis as a craft, and also the notion of learning
by statistics by apprenticeship. Elsewhere this has been described as a strategy for learning
statistical thinking, as opposed to the statistical machinery taught on most courses.

The book is a wealth of effective and helpful real examples, and includes exercises after
each substantive chapter. It has been beautifully produced. I think the pace and presentation are
exactly right for the intended audience.

International Statistical Review (2010), 78, 2, 316–328
C© 2010 The Authors. Journal compilation C© 2010 International Statistical Institute

SHORT BOOK REVIEWS 327

So it has some good things about it. But (in my opinion!) it also has some bad things. The
authors appear to regard the law of large numbers and the central limit theorem as the same thing
(e.g., p266 “the Law of Large Numbers, which is also known as the Central Limit Theorem”).
The words “nonparametric” and “distribution-free” do not appear in the index, and I did not
spot them in the body of the book. Surely this is a major omission, as nonparametric methods
are widely used in the social sciences. The book refers to the “controversy” over the relationship
between levels of measurement and choice of statistical technique. But I would suggest that
this controversy has evaporated with the recognition of the distinction between pragmatic and
representational aspects of measurement. Of all the sections of the book, I found this discussion
the weakest – which is a little disappointing since measurements of both types figure large
in the social sciences. The book adopts an entirely frequentist perspective, with just one page
mentioning the alternative Bayesian view – but I am afraid I found that description unconvincing
since the description of subjective probability was rather confused. Given the huge progress in
practical application of Bayesian methods, I think this topic deserved better. Put together, such
criticisms mean the book has a rather old-fashioned feel, in terms of statistical methodology.

There is some discussion of missing data, but I would have liked more on this and indeed on
data quality in general. I recognize that this is something of a hobby horse of mine but, after
all, the first thing students discover when they step out of the classroom and have to apply their
hard-won statistical expertise in practice is that the data facing them are not as clean as the data
on which they have been practicing. The real world is a messy place, and so are real data.

Overall, as will probably be obvious, I found the book rather frustrating. While there is a lot
I like about it, I found the lack of rigor – to the extent of quite often saying things that I would
argue are wrong – grating. It might not matter to a student for whom this is the only statistics
course they ever study, and who never uses statistics in later life, but presumably the authors
hope that many of the readers will go on to use the ideas and tools.

David J. Hand: d.j.hand@imperial.ac.uk
Mathematics Department, Imperial College
London SW7 2AZ, UK

Foundations of Factor Analysis, Second Edition
Stanley A. Mulaik
Chapman & Hall/CRC, 2009, xxiv + 524 pages, £ 39.99 / US$ 79.95, hardcover
ISBN: 978-1-4200-9961-4

Table of contents

1. Introduction 9. Other models of factor analysis
2. Mathematical foundations for factor analysis 10. Factor rotation
3. Composite variables and linear transformations 11. Orthogonal analytic rotation
4. Multiple and partial correlations 12. Oblique analytic rotation
5. Multivariate normal distribution 13. Factor scores and factor indeterminacy
6. Fundamental equations of factor analysis 14. Factorial invariance
7. Methods of factor extraction 15. Confirmatory-factor analysis
8. Common-factor analysis

Readership: Researchers and graduate students interested in fundamental issues of factor
analysis.

The first sentence of the Preface says it all: “This is a book for those who want or need to get
to the bottom of things.” The first edition of this book appeared almost 40 years ago. It began

International Statistical Review (2010), 78, 2, 316–328
C© 2010 The Authors. Journal compilation C© 2010 International Statistical Institute

328 SHORT BOOK REVIEWS

with a bit more mysterious sentence: “When I was nine years old, I dismantled the family alarm
clock.”

I must say that I am very happy that the author has taken the challenge to update and revise
this precious book into the second edition. It will be an important source for decades to come.
Although many topics in the first version still remain relevant, there are good grounds for
the new edition, mostly due to the development of factor analysis, which has (again) taken huge
steps since 1972. The history of factor analysis is very long and rather complicated. Therefore
it is quite natural that the usual books do not necessarily help in understanding where all the
equations and different procedures actually came from. But, this is not a usual book.

As its title suggests, it digs deep into the foundations of factor analysis, shedding light
on dozens of questions concerning models, estimation, interpretation, generally applied rules,
various algorithms and backgrounds of things, even philosophical and historical notes, etc. All
this, together with some jokes here and there, makes reading the book like following a series of
enjoyable lectures.

All the way the topics are explained clearly, and mathematics is taught, as it is needed
to understand a derivation of an equation or some procedure. Although there are numerous
equations and formulas, there is also a great deal of words explaining them and offering more
insight. Overall, the book is worth having nearby if you find yourself facing serious questions
like “why?” or “who?” or “how?” related to factor analysis.

Kimmo Vehkalahti: kimmo.vehkalahti@helsinki.fi
Department of Social Research

FI-00014 University of Helsinki, Finland

International Statistical Review (2010), 78, 2, 316–328
C© 2010 The Authors. Journal compilation C© 2010 International Statistical Institute

Copyright of International Statistical Review is the property of Wiley-Blackwell and its content may not be

copied or emailed to multiple sites or posted to a listserv without the copyright holder’s express written

permission. However, users may print, download, or email articles for individual use.

Introduction

True vertigo is a type of vertigo identified by failing to
sense gravity and spinning feeling. The patient might
have hallucinations of self or surroundings’ motion
(Marple and Meyerhoff, 1998). Currently, there are
various methods for treating patients with vertigo such
as drug, surgery, and vestibular rehabilitation (Gananca
et al., 2002; Girardi and Konrad, 2005). Treatments in
the emergency department are symptomatic and aim to
eliminate vertigo and other accompanying symptoms
(Kerber, 2009).

Diazepam as a benzodiazepine compound plays a
major role in treatment of disorders with central origin.
It has also been effective in vertigo treatment as shown
in various studies. This drug, as a gamma-aminobutyric
acid (GABA) receptor regulator, centrally leads to
inhibition of vestibular response. In low doses, this
drug is very effective and beneficial. However, its
addictiveness, bringing about memory problems, and
increasing the chance of falling for the patient are

among the limitations of its consumption. These might
be the reasons that researchers are looking for
replacement methods and treatments (Tan et al., 2014).
Antihistamine, anticholinergic, and anti-nausea drugs
have been suggested for this purpose (Hain and Uddin,
2003; Hain and Yacovino, 2005).

On the other hand, hyoscine is one of the oldest
medicines. This drug is extracted from a plant called
henbane from the family of Solanaceae. Hyoscine is an
anticholinergic, antispasmodic, analgesic and sedative
drug that exerts its relaxing effect directly on smooth
muscles. In addition to its peripheral anticholinergic
activities, this drug also affects the central nervous
system and has a slow but long sedative effect on the
brain (King et al., 2014; Renner et al., 2005). Hyoscine is
one of the most commonly used drugs for motion
sickness and it has been suggested that it might also be
effective in treating or decreasing vertigo symptoms. A
systematic review showed that very few studies have
been carried out to assess the role of hyoscine in
treatment of balance disorders and the existing

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Journal homepage: www.banglajol.info

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Abstract
The present study was a double-blind clinical trial to compare the efficiency
of hysocine and diazepam in vertigo treatment. Eligible patients (n=69) were
randomly divided into 2 groups of 5 mg hyoscine and 10 mg diazepam.
Severity of vertigo was measured in supine and sitting position, and while
turning the head. Vertigo severity was assessed before, and 1 and 2 hours
after administration of the drug. Treatment success rate of diazepam in
relieving vertigo in different positions varied between 88.9 and 100%, while
this rate was 31.2–73.5% in hyoscine treatment group (p<0.01). Prescription of diazepam led to complete relief of vertigo in 40–63% of the patients, while this rate was only 2.6–12.5% in hyoscine treatment group (p<0.001). It is likely that diazepam is a better option than hyoscine for management of true vertigo in patients presenting to the emergency department.

Article Info
Received: 13 October 2016
Accepted: 16 March 2017
Available Online: 3 April 2017

DOI: 10.3329/bjp.v12i2.29962

Cite this article:
Kariman H, Vajihi F, Amini A, Shah-
rami A, Arhami-Dolatabadi A, Sho-
jaee M, Baratloo A. Hyoscine versus
diazepam for the management of true
vertigo in the emergency department.
Bangladesh J Pharmacol. 2017; 12: 95-
100.

Hyoscine versus diazepam for the management of true vertigo in
the emergency department

Hamid Kariman1, Firoozeh Vajihi1, Afshin Amini1, Ali Shahrami1, Ali Arhami-Dolatabadi1,
Majid Shojaee1 and Alireza Baratloo2

1Department of Emergency Medicine, Imam Hossein Hospital, Shahid Beheshti University of Medical Sciences, Tehran,
Iran; 2Department of Emergency Medicine, Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran.

C
lin

ic
al

T
ri

al

This work is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, distribute and pe r-
form the work. You must attribute the work in the manner specified by the author or licensor

evidence and conclusions regarding effectiveness of this
drug in reducing vertigo symptoms and motion
sickness are mostly based on animal studies and second
or third class evidence. As a result, they had suggested
carrying out more studies in this field (Spinks et al.,
2011). Therefore, the present clinical trial was designed
aiming to evaluate the effectiveness of hyoscine com-
pared to diazepam in management of true vertigo in
patients presenting to the emergency department.

Materials and Methods

Study design and setting

The present study is a double-blind clinical trial
performed during 6 months, from March 2015 to
September 2015, in Imam Hossein Hospital, Tehran,
Iran. The main goal of the study was comparing the
effectiveness of hyoscine with 5 mg dose and 10 mg
diazepam in managing and relieving vertigo.

Participants

All patients over 18 years old with complaint of vertigo,
who were categorized as true vertigo cases based on
clinical definition were included in the study. Receiving
prophylaxis treatment with vertigo reducing drugs,
allergy to hyoscine or diazepam, pregnancy, lactating,
renal failure, and recent visit to the hospital were
considered as exclusion criteria.

Sample size

To determine sample size the formula for comparing
means in analysis of repeated measures was used.
Considering the results of previous studies, sample size
for finding significant difference in mean response of
the 2 groups after drug treatment with a test power of
90% ( =0.9), type 1 error of 5% ( =0.05), combined
standard deviation of 18, individual observation
correlation of 0.8 (rho=0.8) and correlation structure of 1
for individual observation was estimated to be 21
patients in each group using the formula. This number
was multiplied by 20% probability of loss to reach the
final sample size of 26 patients in each group.

Randomization and blinding

Solutions were prepared by an emergency medicine
specialist that did not participate in the process of
evaluation and prescription of drugs. They were placed
in similar packs covered by aluminum foil. The
solutions were anonymous and both were diluted in 10
mL distilled water. The solution containing hyoscine
was named pack A, and the one containing diazepam
was named pack B. It should be noted that the compo-
sition of packs was confidential until the end of the
study. To ensure double blinding of the study, prepa-
ring solutions and drug injection and recording the
results were done by 2 separate physicians. Information

regarding the administered drug was only revealed
when adverse side effects or other clinical changes were
seen in a patient that needed knowledge of the
administered drug.

In the present study, randomization was done using
random numbers table. For this purpose, each patient
was given a number; if the number was odd, pack A
was administered and if it was even, pack B was used.

Intervention

Initially, demographic data and baseline characteristics
including age, sex, history of using drugs, duration of
vertigo and history of vertigo were recorded. Patients
were also questioned about accompanying symptoms
including nausea, vomiting, hearing loss, tinnitus, ear
fullness, double vision, blurred vision, dysarthria,
dysphagia, hypoesthesia, paresthesia, and weakness of
one side of the face and extremities. There were also
questions regarding the characteristics of vertigo
including it being spinning or not, its central or
peripheral origin and estimated duration of vertigo.
Presence and direction of nystagmus were other
studied factors. This category was defined in 5 levels of
nystagmus free, horizontal, vertical, and rotary
nystagmus, and other. In addition, before prescription
of drug, the patients’ feeling of vertigo was evaluated in
supine position, while sitting and while turning their
head to one side. After gathering baseline
characteristics and demographic data, patients were
divided into 2 groups of 5 mg hyoscine and 10 mg
diazepam using a random numbers table. After
administration of drug, 500 mL normal saline was
prescribed for the patients.

Outcome

Severity of vertigo was classified as no vertigo, mild,
moderate, and severe vertigo. In the present study, at
least 1 level improvement or relief of vertigo was
defined as successful treatment. The patients’ vertigo
sensation was re-evaluated in supine and sitting
positions and while turning their head to one side in the
first and second hour of drug administration. Probable
side effects of the drugs were monitored since injection
until 2 hours after administration. They were recorded
based on patient’s report and clinical appearance. After
2 hours of follow-up, if vertigo was relieved, the patient
was discharged with approval of the in-charge
physician. In case of unsuccessful treatment, rescue
medication was prescribed by the in-charge physician.

Statistical analysis

Data were entered to SPSS 21 and were analyzed using
STATA 11.0 software. Severity of vertigo and accom-
panying symptoms of the patient on admission, and 1
and 2 hours after treatment initiation were reported as
frequency and percentage. To evaluate the age differ-
ence between the 2 groups, t-test was applied. Duration

96 Bangladesh J Pharmacol 2017; 12: 95-100

of vertigo was compared using Mann-Whitney test. To
compare other baseline characteristics and
demographic data of the patients between the groups
on admission, Chi-squared or Fisher’s exact tests were
used. Non-parametric chi-squared for trend test and
Kaplan-Meier curve were used for comparing the trend
of treatment success between hyoscine and diazepam
groups in the first and second hours after treatment. For
this purpose, at least 1 level improvement in vertigo
severity was considered as successful treatment. In
another part, to be sure of the findings and approve the
analyses, treatment success was considered complete
relief of vertigo and findings were separately reported
in tables and figures. In all analyses, p<0.05 was considered as significance level.

Ethics

Protocol of this study was assessed by the Ethics
Committee of the Shahid Beheshti University of Medi-
cal Sciences and was given the code number
IR.SBMU.SM.REC.1394.134. Patients voluntarily partici-
pated in the study and informed written consent was
obtained from them. Throughout the study, the
researchers adhered to declaration of Helsinki princi-
ples. Protocol of the study was registered on the Iranian
registry of clinical trials located at www.irct.ir under
the code number IRCT2016100815640N5.

Results

Demographic and baseline findings

Finally, 69 patients with the mean age of 55.4 ± 15.7
years (age range: 21-80 years) were included in the
study (68.1% female). 39 patients were treated with
hyoscine and 30 received diazepam. CONSORT
flowchart of studied patients was showed in Figure 1.
Table I shows demographic data and baseline
characteristics of the studied patients and the findings
of clinical examinations based on the groups. According
to the results, there was no significant difference
between mean age of the patients (p=0.57) and their sex
distribution (p=0.18). History of vertigo, characteristics
and type of vertigo, its duration, direction of
nystagmus, and accompanying symptoms were also
similar between the 2 groups (p>0.05).

Treatment effectiveness in supine position

Presence of vertigo in supine position did not show a
significant difference between the 2 groups (p=0.18).
Considering at least one level improvement, after 1
hour, 4 patients in hyoscine group and 12 in diazepam
group reported improvement in supine position
vertigo. These counts were 5 and 16 patients,
respectively, 2 hours after treatment initiation. Non-

parametric Chi-squared for trend test
showed that success rate was significantly
higher in diazepam group compared to
hyoscine treatment group (p<0.001). Complete relief of vertigo was seen in 1 case after hyoscine treatment and 4 after diazepam administration in the first hour. After 2 hours, these values were 2 and 11 patients, respectively (p=0.001).

Treatment effectiveness in sitting position

Presence of vertigo in sitting position on
admission did not show a significant differ-
ence between the 2 groups on admission
(p=0.99). Considering at least 1 level
improvement in vertigo in sitting position,
after 1 hour, 26 patients in hyoscine group
and 27 in diazepam group reported feeling
better regarding vertigo. These values were
30 and 29 patients, respectively, after 2
hours. Non-parametric Chi-squared for
trend test showed that success rate was
significantly higher in diazepam group
compared to hyoscine treatment group
(p=0.02). Hyoscine administration could
completely relieve vertigo in sitting position
in the first hour. However, 2 hours after
injection, vertigo was completely relieved
for 1 patient in hyoscine group and 12
patients in diazepam group (p=0.001).

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si
s

E
nr

ol
lm

en
t

Hyoscine

Allocated to intervention (n = 39)

Received allocated intervention (n
= 0)

Did not receive allocated interven-
tion (n = 0)

Lost to follow-up (n = 0)

Discontinued intervention
(n = 0)

Excluded (n = 2)

Refused to participate (n = 4)

Randomized (n = 69)

Assessed for eligibility (n = 75)

Diazepam

Allocated to intervention (n = 30)

Received allocated intervention (n
= 0)
Did not receive allocated interven-
tion (n = 0)

Analyzed (n = 39)

Excluded from analysis
(n = 0)

Lost to follow-up (n = 0)
Discontinued intervention
(n = 0)

Analyzed (n = 30)

Excluded from analysis
(n = 0)

Figure 1: CONSORT flowchart of studied patients

Bangladesh J Pharmacol 2017; 12: 95-100 97

http://www.irct.ir

Treatment effectiveness while turning the head

Presence of vertigo while turning the head did not
show a significant difference between the 2 groups on

admission (p=0.78). Considering at least 1 level
improvement in vertigo while turning the head, after 1
hour 21 patients in hyoscine group and 21 in diazepam
group reported feeling improvement in their vertigo.
These values were 25 and 27 patients, respectively, after
2 hours. Non-parametric Chi-squared for trend test
showed that success rate was significantly higher in
diazepam group compared to hyoscine treatment group
(p=0.03). Hyoscine administration could not completely
relieve vertigo for any patients in the first hour.
However, diazepam administration led to complete
relief of 3 patients during this time. In addition, 2 hours
after drug administration vertigo was completely
relieved in 4 patients in hyoscine group and 17 cases in
diazepam group.

Table II depicts the results in terms of effectiveness of
hyoscine and diazepam administration in treatment of
vertigo in supine position, in sitting position and while
turning the head. Figure 2 presents complete vertigo
relief failure rate of hyoscine and diazepam in treating
vertigo in various positions.

Side effects

In evaluation of treatment side effects, follow-up did
not reveal any side effect of drug administration.

Discussion

Findings of the present study showed that efficiency of
diazepam is significantly higher than hyoscine in
treatment of vertigo and its symptoms. Treatment
success rate of diazepam in relieving vertigo in
different positions varied between 88.9 and 100%, while
this rate was 31.2–73.5% in hyoscine treatment group.
Prescription of diazepam led to complete relief of
vertigo in 40–63% of the patents, while this rate was
only 2.6–12.5% in hyoscine treatment group.

Although hyoscine, as an anticholinergic drug, has been
used for a long time and in various clinical settings,
effectiveness of this drug in controlling true vertigo has
been evaluated in few studies. For instance, a syste-

Table I

Demographic data and baseline characteristics

Variable

Hyoscine
(n = 39)

Diazepam
(n = 30)

P

Age (year) 54.5 56.6 0.57

Sex

Female 24 23 0.18

Male 15 7

History of underlying
illness

17 14 0.80

History of vertigo 3 2 0.99a

Vertigo characteristic

Spinning 36 24 0.16a

Non-spinning 3 6

Type of vertigo

Central 9 10 0.34

Peripheral 30 20

Duration of vertigo
(hours)

4 3.5 0.99b

Vertigo symptoms

Nausea 34 27 0.99a

Vomiting 31 25 0.76a

Dysarthria 2 2 0.99a

Dysphagia 1 0

Hyposthesia 1 0

Tinnitus 0 1

Nystagmus

No 4 6 0.50a

Horizontal 31 21

Horizontal-vertical 4 3

aBased on Fisher’s exact test; bbased on Mann-Whitney test

Analysis time

0 1 2 3

Kaplan-Meier failure estimates A
1.00

0.75

0.50

0.25

0.00

Number at risk
Hyscine 16 15 14 14
Diazepam 18 14 7 7

Hyoscine Diazepam

Time (hour)

B

Number at risk
Hyscine 39 39 36 36
Diazepam 30 30 18 18

Hyoscine Diazepam

Kaplan-Meier failure estimates

1.00

0.75

0.50

0.25

0.00
Time (hour)

C

Number at risk
Hyscine 34 34 30 30
Diazepam 27 24 10 10

Hyoscine Diazepam
Kaplan-Meier failure estimates
1.00

0.75

0.50

0.25

0.00

0 1 2 3 0 1 2 3

Figure 2: Complete vertigo relief failure rate of hyoscine and diazepam in treating vertigo in supine position (A), in sitting position
(B), and while turning the head (C)

98 Bangladesh J Pharmacol 2017; 12: 95-100

matic review on 35 studies in 2011 aiming to assess the
efficacy of transdermal hyoscine in motion sickness
symptom relief showed that although this drug is
effective in relieving the symptoms of this problem, all
the evidence obtained are level 2 and 3 evidence and
this makes it hard to reach a final decision regarding
use of this drug in treating vertigo and motion sickness
(Spinks et al., 2011). Even three decades ago, Rahko and
Karma also attempted to evaluate treatment value of
transdermal hyoscine in treatment of peripheral vertigo
in 30 patients. This study showed that using this treat-
ment brings about desirable outcome in reducing symp-
toms of Menier’s disease. However, the researchers
stated that blurred vision and dry mouth are observed
side effects of this drug. Finally, they concluded that
transdermal hyoscine could be used as a replacement
option in treatment of peripheral vertigo (Rahko and
Karma, 1985). The reason for the contradicting results
obtained in this study, compared to other studies,
might be the route of administration. All the mentioned
studies had evaluated the effectiveness of transdermal
hyoscine in relieving vertigo symptoms. The effects of
systemic and local administration of a drug might be
significantly different.

Findings of the present study show the acceptable
effectiveness of diazepam in treatment of acute vertigo.
Findings of other studies are also indicative of the same
result. For example, Ganança et al. in their study
showed that clonazepam leads to complete relief of

vertigo in 77.4% of vertigo patients (Gananca et al.,
2002). In another clinical trial lorazepam and
dimenhydrinate were compared for treatment of
vertigo in patients. Findings of the study also confirmed
the effectiveness of lorazepam in vertigo symptom
relief and walking of the patients (Marill et al., 2000).
Although a study by Amini et al. showed that
promethazine is more efficient than lorazepam in
treating vertigo, its findings also indicated the effective-
ness of lorazepam in this regard (Amini et al., 2014).

Conclusion

It is likely that diazepam is a better option than
hyoscine for management of true vertigo in patients
presenting to emergency department.

Conflict of Interest

All authors have completed the ICMJE uniform disclosure
form and declare no support from any organization for the
submitted work.

Acknowledgement

The authors appreciate the cooperation of the Emergency
Department staff of Imam Hossein and Shohadaye Tajrish
Hospitals, Tehran, Iran.

Table II

Effectiveness of hyoscine and diazepam prescription in treatment of vertigo in different positions

Variable In supine position In sitting position While turning the head

Hyoscine
(n = 39)
Diazepam
(n = 30)

p
value

Hyoscine
(n = 39)
Diazepam
(n = 30)
p
value
Hyoscine
(n = 39)
Diazepam
(n = 30)
p
value

On admission

None 23 12 0.18a 0 0 0.99a 5 3 0.78a

Mild 10 8 1 1 2 1

Moderate 0 1 1 0 0 0

Severe 6 9 37 29 32 26

An hour after
treatment

None 24 16
—

0 0
—

5 6
—

Mild 10 11 1 10 4 8

Moderate 3 2 27 17 20 12

Severe 2 1 11 3 10 4

Two hours after
treatment

None 25 23
—

3 12
—

9 20
—

Mild 10 6 2 3 4 2

Moderate 0 1 28 14 19 8

Severe 4 0 6 1 7 0

aBased on Fisher’s exact test

Bangladesh J Pharmacol 2017; 12: 95-100 99

Author Info
Firoozeh Vajihi (Principal contact)
e-mail: f.vajihi@yahoo.com

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