Dr Lex Rutten started as a general practitioner in conventional
medicine in 1978, but soon became interested in homeopathy as an
addition to conventional medicine. Studying statistics the author
discovered Bayes' theorem as a real eye-opener: this is how
experience works. He published dozens of scientific papers and
teaches homeopathy and research in the Netherlands, India and
Argentina. He developed a protocol for clinical research and
organised the first prospective validation of symptoms in
Dr Martine is an assistant professor at Delft Technical University.
Her PhD thesis was titled "Moisture in the topsoil, from large-scale
observations to small scale process understanding" and her
specialty is water management. She has vast experience in
teaching statistics and methodology of research.
In recent times evidence based medicine is an important component
of medicine. Homeopathy is a scientific system of medicine where
prescribing a medicine is an art based on symptoms/syndromes.
Several were recorded/observed more than 200 years ago. There
are more than 600 thousand homeopathic physicians in the world
who are treating millions of patients with varying success but the
data collection and interpretation is challenging. This is because
the majority have an inadequate knowledge of statistics and also
the books available on biostatistics are only partially helpful as
they lack the homeopathic perspective.
This book explains statistics in plain language and is written from
homeopathic standpoint, thus bridging the gap between practitioner
and scientist. The renowned first author has more than 35 years of
experience in this field and has published many scientific papers
in international journals and this book is a compendium of years
of arduous work. The terminology used in statistics has been well
explained with examples and the exercises given at the end of
each chapter are written in a thought provoking style.
This book is a requisite for applying statistics to identify
homeopathic symptoms as prognostic factors from the colossal
and indeterminate data we built up in two centuries. This will
serve as a tangible base for planning randomised controlled trials
and modifying and modernising the homeopathic repertory in future.
I highly recommend this book for every homeopathic student and practitioner worldwide.
Clinical experience is the core of homeopathy. Homeopathic
medicine is based on experience gathered by a large number
of homeopathic practitioners. This book is an attempt to bring
Statistics and clinical research closer to homeopathic doctors
and students in homeopathic medicine. Nowadays the computer
enables us to enter large amounts of new data in our Materia
Medica and Repertories with little effort. This has advantages and
disadvantages. Large numbers can provide more certainty about
correctness and reliability of symptoms that indicate specific
medicines. However, we should be careful not to introduce
misleading data by biased observations or by misinterpretation of
the data. Why is a specific symptom an indication for a specific
homeopathic medicine and how sure are we about the validity of
This brings us to statistics. Statistics, especially Bayesian statistics,
offers us an instrument to use experience to predict future outcome,
like a curative effect of a medicine. Since the nineteenth century
there has been a rapid development in understanding how the
human organism works. This seemed to give us certainty, at least
in conventional medicine: if we understood how a medicine works,
we thought we knew when it worked. It becomes increasingly clear
that this worldview has limitations. Non-conventional methods,
like homeopathy, are not understood in this way. Understanding
the mechanism of action appeared not to be sufficient in living
Systems: you cannot separate one organ from the rest of the body.
All organs, mind and body, interact with each other. This is still
far from being fully understood, and probably the reason why
experience-based medical methods, like homeopathy, are still
necessary. By the way, experience never parted from conventional
medicine either. Many treatments of conventional medicine are
still based on experience and consensus between doctors.
Experience, however, can be misleading because of variation:
many phenomena do not appear in every human being, and if
they appear, they may appear temporarily. Furthermore, our
observations, or our interpretation of these observations, are
always subjective and often not correct. In homeopathy we
learned to combine different observations and symptoms. The
combination of symptoms and characteristics of the patient gives
us more or less certainty that a medicine is going to have an effect.
Sometimes we are surer about it than others. Bayesian statistics
provides a mathematical model for this (un)certainty.
First of all, we do not want to present a complete course in
statistics, but just an elementary introduction how to understand
data. Perhaps you want to collect and analyse data from your own
practice yourself with a spreadsheet program. The spreadsheet can
produce mean, median, standard error and confidence interval,
but then you must understand what those numbers mean. If you
publish your data in a way which your colleagues should be able
to understand and reproduce them.
**Contents and Sample Pages**
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